@article {43296,
	title = {Enhancing Questioning Skills through Child Avatar Chatbot Training with Feedback},
	journal = {Frontiers in Psychology},
	year = {2023},
	publisher = {Frontiers},
	doi = {10.3389/fpsyg.2023.1198235},
	author = {Ragnhild K. {R{\o}ed} and Gunn Astrid {Baugerud} and Syed Zohaib {Hassan} and Saeed Shafiee {Sabet} and Salehi, Pegah and Powell, Martine and Riegler, Michael and Halvorsen, P{\r a}l and Miriam Sinkerud {Johnson}}
}
@inproceedings {43282,
	title = {Generation of Synthetic Tabular Healthcare Data Using Generative Adversarial Networks},
	journal = {International conference on multimedia modeling},
	year = {2023},
	publisher = {Springer International Publishing},
	abstract = {High-quality tabular data is a crucial requirement for developing data-driven applications, especially healthcare-related ones, because most of the data nowadays collected in this context is in tabular form. However, strict data protection laws complicates the access to medical datasets. Thus, synthetic data has become an ideal alternative for data scientists and healthcare professionals to circumvent such hurdles. Although many healthcare institutions still use the classical de-identification and anonymization techniques for generating synthetic data, deep learning-based generative models such as generative adversarial networks (GANs) have shown a remarkable performance in generating tabular datasets with complex structures. This paper examines the GANs{\textquoteright} potential and applicability within the healthcare industry, which often faces serious challenges with insufficient training data and patient records sensitivity. We investigate several state-of-the-art GAN-based models proposed for tabular synthetic data generation. Healthcare datasets with different sizes, numbers of variables, column data types, feature distributions, and inter-variable correlations are examined. Moreover, a comprehensive evaluation framework is defined to evaluate the quality of the synthetic records and the viability of each model in preserving the patients{\textquoteright} privacy. The results indicate that the proposed models can generate synthetic datasets that maintain the statistical characteristics, model compatibility and privacy of the original data. Moreover, synthetic tabular healthcare datasets can be a viable option in many data-driven applications. However, there is still room for further improvements in designing a perfect architecture for generating synthetic tabular data.},
	keywords = {deep learning, Medical data, synthetic data generation},
	doi = {10.1007/978-3-031-27077-2_34},
	author = {Alireza Hossein Za {Nik} and Riegler, Michael and Halvorsen, P{\r a}l and Stor{\r a}s, Andrea}
}
@inproceedings {43256,
	title = {Identifying Important Proteins in Meibomian Gland Dysfunction with Explainable Artificial Intelligence},
	journal = {IEEE International Symposium on Computer-Based Medical Systems (IEEE CBMS2023)},
	year = {2023},
	abstract = {Meibomian gland dysfunction is the most common cause of dry eye disease, which is a prevalent condition that can damage the ocular surface and cause reduced vision and substantial pain. Meibum secreted from the meibomian glands makes up the majority of the outer, protective lipid layer of the tear film. Changes in the secreted meibum and markers of glandular damage can be detected through tear sampling.Several studies have investigated the tear film protein expression in meibomian gland dysfunction, but less work apply machine learning to analyze the protein patterns.\&nbsp;We use machine learning and methods from explainable artificial intelligence to detect potential clinically relevant proteins in meibomian gland dysfunction. Two different explainable artificial intelligence methods are compared. Several of the proteins found important in the models have been linked to dry eye disease in the past, while some are novel. Consequently, explainable artificial intelligence methods serve as a promising tool for screening for proteins that are relevant for meibomian gland dysfunction. By doing so, one may be able to discover new biomarkers and treatments, and gain a better understanding of how diseases develop.},
	keywords = {Dry eye disease, Explainable artificial intelligence, Machine learning, meibomian gland dysfunction, proteomics},
	author = {Stor{\r a}s, Andrea and Magn{\o}, Morten and Fineide, Fredrik and Thiede, Bernd and Chen, Xiangjun and Str{\"u}mke, Inga and Halvorsen, P{\r a}l and Utheim, Tor and Riegler, Michael}
}
@article {42995,
	title = {Live Streaming Technology and Online Child Sexual Exploitation and Abuse - A Scoping Review},
	journal = {Trauma, Violence, \& Abuse},
	year = {2023},
	publisher = { SAGE Publications},
	abstract = {Livestreaming of child sexual abuse is an established form of online child sexual exploitationand abuse. However, only a limited body of research has examined this issue. The Covid-19pandemic has accelerated internet use and user knowledge of livestreaming servicesemphasising the importance of understanding this crime. In this scoping review, existingliterature was brought together through an iterative search of eight databases containing peer-reviewed journal articles, as well as grey literature. Records were eligible for inclusion if theprimary focus was on livestream technology and online child sexual exploitation and abuse,the child being defined as eighteen years or younger. Fourteen of the 2,218 records wereselected. The data were charted and divided into four categories: victims, offenders,legislation, and technology. Limited research, differences in terminology, study design, andpopulation inclusion criteria present a challenge to drawing general conclusions on thecurrent state of livestreaming of child sexual abuse. The records show that victims arepredominantly female. The average livestream offender was found to be older than theaverage online child sexual abuse offender. Therefore, it is unclear whether the findings arerepresentative of the global population of livestream offenders. Furthermore, there appears tobe a gap in what the records show on platforms and payment services used and current digitaltrends. The lack of a legal definition and privacy considerations pose a challenge toinvestigation, detection, and prosecution. The available data allow some insights into apotentially much larger issue.},
	author = {Catharina Sofie Rode {Drejer} and Riegler, Michael and Miriam Sinkerud {Johnson} and Halvorsen, P{\r a}l and Gunn Astrid {Baugerud}}
}
@inproceedings {43336,
	title = {Man vs. AI: An in silico study of polyp detection performance},
	journal = {2023 IEEE 36th International Symposium on Computer-Based Medical Systems (CBMS)},
	year = {2023},
	publisher = {IEEE},
	address = {L{\textquoteright}Aquila, Italy},
	abstract = {AI-based colon polyp detection systems have received much attention, and several products and prototypes report good results. In silico verification is a crucial step when developing such systems, but very few compare human versus AI performance. This paper, therefore, describes methods and results for an in silico test of an AI model with two different versions for polyp detection in colonoscopy and compares them to the performance of endoscopist doctors who reviewed the same colonoscopy video clips. The two versions have different thresholds for false positive rate reduction. Our models perform polyp detection within the range of the endoscopists{\textquoteright} performance, although faster, showing a potential for use in a clinical setting. For the AI and the endoscopists alike, the results show a trade-off between high sensitivity and high specificity; to achieve perfect detection, one will also get abundance of false positives. This can cause alarm fatigue in a clinical setting.\&nbsp;},
	doi = {10.1109/CBMS58004.2023.00307},
	url = {https://ieeexplore.ieee.org/document/10178833},
	author = {Pia H. {Smedsrud} and Espeland, H{\r a}vard and Tor Jan Derek {Berstad} and Petlund, Andreas and de Lange, Thomas and Riegler, Michael and Halvorsen, P{\r a}l}
}
@article {ali2021polypgen,
	title = {A multi-center polyp detection and segmentation dataset for generalisability assessment},
	journal = {Nature Scientific Data},
	volume = {10},
	year = {2023},
	publisher = {Nature},
	doi = {https://doi.org/10.1038/s41597-023-01981-y},
	url = {https://doi.org/10.1038/s41597-023-01981-y},
	author = {Ali, Sharib and Jha, Debesh and Ghatwary, Noha and Realdon, Stefano and Cannizzaro, Renato and Osama E {Salem} and Lamarque, Dominique and Daul, Christian and Kim V {Anonsen} and Riegler, Michael and Kim V. {{\r A}nonsen} and Petlund, Andreas and Halvorsen, P{\r a}l and Rittscher, Jens and de Lange, Thomas and James E. {East}}
}
@inproceedings {43077,
	title = {Multimedia datasets: challenges and future possibilities},
	journal = {International conference on multimedia modeling},
	year = {2023},
	doi = {https://doi.org/10.1007/978-3-031-27818-1_58},
	author = {Nguyen, Thu and Stor{\r a}s, Andrea and Thambawita, Vajira and Hicks, Steven and Halvorsen, P{\r a}l and Riegler, Michael}
}
@inproceedings {43320,
	title = {Predicting the degree of meibomian gland dropout with artificial intelligence},
	journal = {ARVO Annual Meeting},
	year = {2023},
	author = {Fineide, Fredrik and Stor{\r a}s, Andrea and Magn{\o}, Morten and Hugo Lewi {Hammer} and Chen, Xiangjun and Khan, Ayyad and Halvorsen, P{\r a}l and Utheim, Tor and Riegler, Michael}
}
@inproceedings {43291,
	title = {ScopeSense: An 8.5-Month Sport, Nutrition, and Lifestyle Lifelogging Dataset},
	journal = {International Conference on Multimedia Modeling (MMM)},
	volume = {13833},
	year = {2023},
	pages = {502 - 514},
	publisher = {Springer International Publishing},
	address = {Cham},
	abstract = {Nowadays, most people have a smartphone that can track their everyday activities. Furthermore, a significant number of people wear advanced smartwatches to track several vital biomarkers in addition to activity data. However, it is still unclear how these data can actually be used to improve certain aspects of people{\textquoteright}s lives. One of the key challenges is that the collected data is often massive and unstructured. Therefore, a link to other important information (e.g., when, what, and how much food was consumed) is required. It is widely believed that such detailed and structured longitudinal data about a person is essential to model and provide personalized and precise guidance. Despite the strong belief of researchers about the power of such a data-driven approach, respective datasets have been difficult to collect. In this study, we present a unique dataset from two individuals performing a structured data collection over eight and a half months. In addition to the sensor data, we collected their nutrition, training, and well-being data. The availability of nutrition data with many other important objectives and subjective longitudinal data streams may facilitate research related to food for a healthy lifestyle. Thus, we present a sport, nutrition, and lifestyle logging dataset called\&nbsp;ScopeSense\&nbsp;from two individuals and discuss its potential use. The dataset is fully open for researchers, and we consider this study as a potential starting point for developing methods to collect and create knowledge for a larger cohort of people.},
	isbn = {978-3-031-27076-5},
	issn = {0302-9743},
	doi = {10.1007/978-3-031-27077-210.1007/978-3-031-27077-2_39},
	url = {https://link.springer.com/content/pdf/10.1007/978-3-031-27077-2https://link.springer.com/content/pdf/10.1007/978-3-031-27077-2.pdfhttps://link.springer.com/10.1007/978-3-031-27077-2_39https://link.springer.com/content/pdf/10.1007/978-3-031-27077-2_39},
	author = {Riegler, Michael and Thambawita, Vajira and Chatterjee, Ayan and Nguyen, Thu and Hicks, Steven and Telle-Hansen, Vibeke and Svein Arne {Pettersen} and Johansen, Dag and Jain, Ramesh and Halvorsen, P{\r a}l},
	editor = {Dang-Nguyen, Duc-Tien and Gurrin, Cathal and Larson, Martha and Alan F. {Smeaton} and Rudinac, Stevan and Dao, Minh-Son and Trattner, Christoph and Chen, Phoebe}
}
@article {43321,
	title = {Usefulness of Heat Map Explanations for Deep-Learning-Based Electrocardiogram Analysis},
	journal = {Diagnostics},
	volume = {13},
	number = {2345},
	year = {2023},
	month = {07/2023},
	publisher = {MDPI},
	abstract = {Deep neural networks are complex machine learning models that have shown promising results in analyzing high-dimensional data such as those collected from medical examinations. Such models have the potential to provide fast and accurate medical diagnoses. However, the high complexity makes deep neural networks and their predictions difficult to understand. Providing model explanations can be a way of increasing the understanding of {\textquotedblleft}black box{\textquotedblright} models and building trust. In this work, we applied transfer learning to develop a deep neural network to predict sex from electrocardiograms. Using the visual explanation method Grad-CAM, heat maps were generated from the model in order to understand how it makes predictions. To evaluate the usefulness of the heat maps and determine if the heat maps identified electrocardiogram features that could be recognized to discriminate sex, medical doctors provided feedback. Based on the feedback, we concluded that, in our setting, this mode of explainable artificial intelligence does not provide meaningful information to medical doctors and is not useful in the clinic. Our results indicate that improved explanation techniques that are tailored to medical data should be developed before deep neural networks can be applied in the clinic for diagnostic purposes.},
	keywords = {electrocardiograms, Explainable artificial intelligence, heat maps},
	doi = {https://doi.org/10.3390/diagnostics13142345},
	author = {Stor{\r a}s, Andrea and Ole Emil {Andersen} and Lockhart, Sam and Thielemann, Roman and Gnesin, Filip and Thambawita, Vajira and Hicks, Steven and Kanters, J{\o}rgen and Str{\"u}mke, Inga and Halvorsen, P{\r a}l and Riegler, Michael}
}
@inproceedings {43255,
	title = {Using explainable artificial intelligence (XAI) to explore factors affecting meibomian gland (MG) dropout},
	journal = {ARVO Annual Meeting},
	year = {2023},
	author = {Stor{\r a}s, Andrea and Fineide, Fredrik and Hugo Lewi {Hammer} and Khan, Ayyad and Magn{\o}, Morten and Xiangjung, Chen and Halvorsen, P{\r a}l and Utheim, Tor and Riegler, Michael}
}
@misc {42446,
	title = {ACM Multimedia Grand Challenge on Detecting Cheapfakes},
	year = {2022},
	note = {https://2022.acmmm.org/call-for-grand-challenge-submissions/},
	publisher = {ACM},
	address = {ACM Multimedia Conference (MM)},
	url = {https://detecting-cheapfakes.github.io},
	author = {Aneja, Shivangi and Midoglu, Cise and Dang-Nguyen, Duc-Tien and Khan, Sohail and Riegler, Michael and Halvorsen, P{\r a}l and Bregler, Chris and Adsumilli, Balu}
}
@article {42768,
	title = {{\'A}ika: A Distributed Edge System for AI Inference},
	journal = {Big Data and Cognitive Computing},
	volume = {6},
	year = {2022},
	month = {Jan-06-2022},
	pages = {68},
	publisher = {MDPI},
	abstract = {Video monitoring and surveillance of commercial fisheries in world oceans has been proposed by the governing bodies of several nations as a response to crimes such as overfishing. Traditional video monitoring systems may not be suitable due to limitations in the offshore fishing environment, including low bandwidth, unstable satellite network connections and issues of preserving the privacy of crew members. In this paper, we present {\'A}ika, a robust system for executing distributed Artificial Intelligence (AI) applications on the edge. {\'A}ika provides engineers and researchers with several building blocks in the form of Agents, which enable the expression of computation pipelines and distributed applications with robustness and privacy guarantees. Agents are continuously monitored by dedicated monitoring nodes, and provide applications with a distributed checkpointing and replication scheme. {\'A}ika is designed for monitoring and surveillance in privacy-sensitive and unstable offshore environments, where flexible access policies at the storage level can provide privacy guarantees for data transfer and access.\&nbsp;},
	doi = {10.3390/bdcc6020068},
	url = {https://www.mdpi.com/2504-2289/6/2/68},
	author = {Joakim Aalstad {Alslie} and Aril Bernhard {Ovesen} and Tor-Arne Schmidt {Nordmo} and H{\r a}vard Dagenborg {Johansen} and Halvorsen, P{\r a}l and Riegler, Michael and Johansen, Dag}
}
@article {28224,
	title = {Artificial intelligence in dry eye disease},
	journal = {The Ocular Surface},
	volume = {23},
	year = {2022},
	month = {Jan-01-2022},
	pages = {74 - 86},
	publisher = {Elsevier},
	abstract = {Dry eye disease (DED) has a prevalence of between 5 and 50\%, depending on the diagnostic criteria used and population under study. However, it remains one of the most underdiagnosed and undertreated conditions in ophthalmology. Many tests used in the diagnosis of DED rely on an experienced observer for image interpretation, which may be considered subjective and result in variation in diagnosis. Since artificial intelligence (AI) systems are capable of advanced problem solving, use of such techniques could lead to more objective diagnosis. Although the term {\textquoteleft}AI{\textquoteright} is commonly used, recent success in its applications to medicine is mainly due to advancements in the sub-field of machine learning, which has been used to automatically classify images and predict medical outcomes. Powerful machine learning techniques have been harnessed to understand nuances in patient data and medical images, aiming for consistent diagnosis and stratification of disease severity. This is the first literature review on the use of AI in DED. We provide a brief introduction to AI, report its current use in DED research and its potential for application in the clinic. Our review found that AI has been employed in a wide range of DED clinical tests and research applications, primarily for interpretation of\&nbsp;interferometry, slit-lamp and\&nbsp;meibography\&nbsp;images. While initial results are promising, much work is still needed on model development, clinical testing and standardisation.},
	keywords = {artificial intelligence, Dry eye disease, Machine learning},
	issn = {15420124},
	doi = {10.1016/j.jtos.2021.11.004},
	url = {https://linkinghub.elsevier.com/retrieve/pii/S1542012421001324},
	author = {Stor{\r a}s, Andrea and Str{\"u}mke, Inga and Riegler, Michael and Grauslund, Jakob and Hugo Lewi {Hammer} and Yazidi, Anis and Halvorsen, P{\r a}l and Kjell G. {Gundersen} and Tor P. {Utheim} and Catherine J. {Jackson}}
}
@inproceedings {gautam2022assisting,
	title = {Assisting Soccer Game Summarization via Audio Intensity Analysis of Game Highlights},
	journal = {Proceedings of 12th IOE Graduate Conference},
	volume = {12},
	year = {2022},
	month = {October},
	pages = {25 {\textendash} 32},
	publisher = {Institute of Engineering, Tribhuvan University, Nepal},
	abstract = {In association football, the development of multimodal summaries is of great importance to both broadcasters and spectators since a large number of viewers choose to follow just the soccer game highlights. The fundamental drive for the development of summarization systems is the requirement to manage huge amounts of data in different formats. By highlighting the most pertinent facts and limiting or omitting unnecessary aspects, summarization helps avoid "information overload." The properties of the audio signals during a particular event can be used to calculate excitement around that event and filter events based on their importance. A root-mean-square (RMS) analysis of audio events was carried out to analyse the excitement across the events in the SoccerNet dataset. It was clearly seen that important events with excitement have a high and distinguishable RMS audio intensity. It was also observed that the generated noise of the crowd was significantly different across various events and if it happened for the home or away team. The intensity was higher for events related to the home team. Likewise, as the wavelet has the benefit of integrating a wave with a specific period, Morlet wavelet analysis was performed for various event types, and the power of the signal across various wavelet scales was analyzed. A distinct signature across various wavelet scales was observed for different events.},
	keywords = {association football, audio signal, soccer game highlights, summarization},
	doi = {http://dx.doi.org/10.13140/RG.2.2.34457.70240/1},
	url = {http://conference.ioe.edu.np/publications/ioegc12/IOEGC-12-004-12009.pdf},
	author = {Gautam, Sushant and Midoglu, Cise and Saeed Shafiee {Sabet} and Dinesh Baniya {Kshatri} and Halvorsen, P{\r a}l}
}
@misc {42443,
	title = {Automatic Thumbnail Selection for Soccer using Machine Learning},
	year = {2022},
	address = {NORA Annual Conference, Stavanger, Norway},
	author = {Husa, Andreas and Midoglu, Cise and Halvorsen, P{\r a}l}
}
@inproceedings {42447,
	title = {Automatic Thumbnail Selection for Soccer Videos using Machine Learning},
	journal = {Proceedings of the 13th ACM Multimedia Systems Conference (MMSys {\textquoteright}22)},
	year = {2022},
	pages = {73-85},
	publisher = {ACM},
	doi = {10.1145/3524273.3528182},
	author = {Husa, Andreas and Midoglu, Cise and Hammou, Malek and Hicks, Steven and Johansen, Dag and Kupka, Tomas and Riegler, Michael and Halvorsen, P{\r a}l}
}
@article {42723,
	title = {Automatic Tracking of the ICSI procedure using Deep Learning},
	journal = {Human Reproduction},
	volume = {37},
	year = {2022},
	month = {07/2022},
	publisher = {Oxford University Press},
	abstract = {Study questionCan deep learning be used to detect and track spermatozoa and the different parts of an ICSI procedure?Summary answerDeep learning can be used as a tool to assist and organize the contents of an ICSI procedure.What is known alreadySperm tracking has been a topic of research and practice for many years, especially in the context of computer-aided sperm analysis (CASA). Recent studies have proposed using deep learning algorithms to track spermatozoa for spermatozoon selection in human and animal samples. One critical part of performing ICSI involves the selection of the {\textquotedblleft}best{\textquotedblright} spermatozoon for injection, but other parts of the procedure may also be of importance. However, as far as we know, tracking using deep learning has not been applied to the ICSI procedure, where detecting instruments and the oocyte could also be helpful in post-analysis and training.Study design, size, durationThe study was performed using three anonymized videos of the ICSI procedure. The frames of the videos were manually annotated by data scientists and verified by an embryologist. The annotations were bounding boxes around specific parts of the ICSI procedure, including sperm, pipettes, and the oocyte. We trained a YOLOv5 model on the collected data, where two videos were used for training and one video for validation.Participants/materials, setting, methodsThe videos of the ICSI procedure were captured at 200x magnification with a DeltaPix camera at Fertilitetssenteret in Oslo, Norway. ICSI was performed using a Nikon ECLIPSE TE2000-S microscope connected with Eppendorf TransferMan 4m micromanipulators. The spermatozoa were immobilised in 5 {\textmu}l Polyvinylpyrrolidone (PVP; CooperSurgical). The videos had a resolution of 1920x1080 and were resized to 640x640 before being processed by the YOLOv5 model. The data will be made public in a later study.Main results and the role of chanceMean average precision (mAP) with the threshold of 0.5 (mAP@.5) is the main quantitative parameter measured in the YOLOv5 model. All the experiments were performed using three-fold cross-validation, where we present the average metrics calculated over the three folds. Overall, the method showed an average mAP@.5 of 0.50 across all predicted classes, which means that the method can track the different components with good accuracy. Looking closer at the individual classes, we see that instruments like the holding pipette and ICSI pipette are detected with high accuracy with a mAP@.5 of 0.87 and 0.94, respectively. The oocyte is also easily tracked with a mAP@.5 of 0.92. The first polar body is well detected with a mAP@.5 of 0.65. The model has issues detecting and tracking individual sperm (both outside and within the pipette), where the method achieved a mAP@.5 of 0.46 for tracking sperm outside the pipette and 0.03 for the sperm inside the pipette. The low score of detecting the sperm in the pipette can be explained by the often unclear visibility of the sperm through the pipette and the low number of training samples.Limitations, reasons for cautionThe limited sample size makes the generalizability of the method difficult to determine. A more extensive evaluation is necessary. Moreover, as the currency study focuses on tracking, patient information and clinical outcome were not included in the analysis.Wider implications of the findingsDeep learning has the potential to aid embryologists to perform successful ICSI through tracking and detection of spermatozoa, pipettes, and the oocyte. This could potentially lead to better internal quality control and teaching possibilities, and hopefully better results.Trial registration numbernot applicable},
	issn = {0268-1161},
	doi = {10.1093/humrep/deac107.261},
	url = {https://academic.oup.com/humrep/article/37/Supplement_1/deac107.261/6619904},
	author = {Hicks, Steven and Thambawita, Vajira and Stor{\r a}s, Andrea and Trine B. {Haugen} and Hugo Lewi {Hammer} and Halvorsen, P{\r a}l and Riegler, Michael and Mette Haug {Stensen}}
}
@inproceedings {42538,
	title = {Automatic Unsupervised Clustering of Videos of the Intracytoplasmic Sperm Injection (ICSI) Procedure},
	journal = {NAIS: Symposium of the Norwegian AI Society },
	volume = {1650},
	year = {2022},
	pages = {1-11},
	publisher = {NAIS 2022},
	abstract = {The\&nbsp;in vitro\&nbsp;fertilization procedure called intracytoplasmic sperm injection can be used to help fertilize an egg by injecting a single sperm cell directly into the cytoplasm of the egg. In order to evaluate, refine and improve the method in the fertility clinic, the procedure is usually observed at the clinic. Alternatively, a video of the procedure can be examined and labeled in a time-consuming process. To reduce the time required for the assessment, we propose an unsupervised method that automatically clusters video frames of the intracytoplasmic sperm injection procedure. Deep features are extracted from the video frames and form the basis for a clustering method. The method provides meaningful clusters representing different stages of the intracytoplasmic sperm injection procedure. The clusters can lead to more efficient examinations and possible new insights that can improve clinical practice. Further on, it may also contribute to improved clinical outcomes due to increased understanding about the technical aspects and better results of the procedure. Despite promising results, the proposed method can be further improved by increasing the amount of data and exploring other types of features.},
	keywords = {clustering, Computer Vision and Pattern Recognition (cs.CV), human reproduction, medical videos, Unsupervised learning},
	isbn = {978-3-031-17029-4},
	doi = {10.1007/978-3-031-17030-0_9},
	author = {Stor{\r a}s, Andrea and Riegler, Michael and Trine B. {Haugen} and Thambawita, Vajira and Hicks, Steven and Hugo Lewi {Hammer} and Kakulavarapu, Radhika and Halvorsen, P{\r a}l and Stensen, Mette}
}
@inproceedings {43064,
	title = {A Comparative Study of Interactive Environments for Investigative Interview of A Virtual Child Avatar},
	journal = {IEEE international symposium on multimedia (ISM)},
	year = {2022},
	pages = {194-201},
	publisher = {IEEE},
	doi = {10.1109/ISM55400.2022.00043},
	author = {Syed Zohaib {Hassan} and Saeed Shafiee {Sabet} and Salehi, Pegah and Ko, Hayley and Riiser, Ingvild and Miriam Sinkerud {Johnson} and Gunn Astrid {Baugerud} and Riegler, Michael and Halvorsen, P{\r a}l}
}
@inproceedings {42709,
	title = {Comparison of Crowdsourced and Remote Subjective User Studies: A Case Study of Investigative Child Interviews},
	journal = {The 14th International Conference on Quality of Multimedia Experience},
	year = {2022},
	publisher = {IEEE},
	doi = {10.1109/QoMEX55416.2022.9900900},
	url = {https://ieeexplore.ieee.org/document/9900900},
	author = {Saeed Shafiee {Sabet} and Midoglu, Cise and Syed Zohaib {Hassan} and Salehi, Pegah and Riegler, Michael and Griwodz, Carsten and Halvorsen, P{\r a}l}
}
@inproceedings {42725,
	title = {Estimating Predictive Uncertainty in Gastrointestinal Polyp Segmentation},
	journal = {2022 IEEE 35th International Symposium on Computer-Based Medical Systems (CBMS)},
	year = {2022},
	pages = {44-49},
	publisher = {IEEE},
	address = {Shenzen, China},
	abstract = {Deep neural networks have achieved state-of-the-art performance on numerous applications in the medical field, with use-cases ranging from automation of mundane tasks to diagnosis of life-threatening diseases. Despite these achievements, deep neural networks are considered {\textquotedblleft}black boxes{\textquotedblright} due to their complex structure and general lack of transparency in their decision-making process. These attributes make it challenging to incorporate deep learning into existing clinical workflows as decisions often need more support than blind faith in a statistical model. This paper presents an investigation of uncertainty estimation for the detection of colon polyps using deep convolutional neural networks (CNNs). We experiment with two different approaches to measure uncertainty, Monte Carlo (MC) dropout and deep ensembles, and discuss the advantages and disadvantages of both methods in terms of computational efficiency and performance gain. Furthermore, we apply the two uncertainty methods to two different state-of-the-art CNN-based polyp segmentation architectures. The uncertainty is visualized as heatmaps on the input images and can be used to make more informed decisions on whether or not to trust a model{\textquoteright}s predictions. The results show that the predictive uncertainties provide a comparison between different models{\textquoteright} predictions which can be interpreted as contrastive explanations where the values are largely influenced by the degree of independence between the models in the ensemble. We also reveal that MC dropout is shown to lack at providing contrastive uncertainty values due to the high correlation between the models{\textquoteright} in the ensemble.},
	doi = {10.1109/CBMS55023.2022.00015},
	url = {https://ieeexplore.ieee.org/document/9867012/http://xplorestaging.ieee.org/ielx7/9866947/9866899/09867012.pdf?arnumber=9867012},
	author = {Jacobsen, Felicia and Hicks, Steven and Halvorsen, P{\r a}l and Riegler, Michael}
}
@article {hicks2022evaluation,
	title = {On evaluation metrics for medical applications of artificial intelligence},
	journal = {Scientific Reports},
	volume = {12},
	number = {1},
	year = {2022},
	pages = {1{\textendash}9},
	publisher = {Nature Publishing Group},
	author = {Hicks, Steven and Str{\"u}mke, Inga and Thambawita, Vajira and Hammou, Malek and Riegler, Michael and Halvorsen, P{\r a}l and Parasa, Sravanthi}
}
@inproceedings {43138,
	title = {Experiences and Lessons Learned from a Crowdsourced-Remote Hybrid User Survey Framework},
	journal = {2022 IEEE International Symposium on Multimedia (ISM)},
	year = {2022},
	pages = {161-162},
	publisher = {IEEE},
	address = {Italy},
	abstract = {Subjective user studies are important to ensure the fidelity and usability of systems that generate multimedia content. Testing how end-users and domain experts perceive multimedia assets might provide crucial information. In this paper, we present our experiences with the open source hybrid crowdsourced-remote user survey framework called Huldra, which is intended for conducting web-based subjective user studies and aims to integrate the individual benefits associated with traditional, crowdsourced, and remote methods. We disseminate our experiences and insights from two actively deployed use cases and discuss challenges and opportunities associated with using Huldra as a framework for conducting user studies.},
	doi = {10.1109/ISM55400.2022.00035},
	url = {https://ieeexplore.ieee.org/document/10019678},
	author = {Midoglu, Cise and Stor{\r a}s, Andrea and Saeed Shafiee {Sabet} and Hammou, Malek and Hicks, Steven and Str{\"u}mke, Inga and Riegler, Michael and Griwodz, Carsten and Halvorsen, P{\r a}l}
}
@inproceedings {42464,
	title = {Explainability methods for machine learning systems for multimodal medical datasets: research proposal},
	journal = {ACM Multimedia Systems (MMSys) Conference},
	year = {2022},
	pages = {347-351},
	publisher = {ACM},
	abstract = {This paper contains the research proposal of Andrea M. Stor{\r a}s that was presented at the MMSys 2022 doctoral symposium. Machine learning models have the ability to solve medical tasks with a high level of performance, e.g., classifying medical videos and detecting anomalies using different sources of data. However, many of these models are highly complex and difficult to understand. Lack of interpretability can limit the use of machine learning systems in the medical domain. Explainable artificial intelligence provides explanations regarding the models and their predictions. In this PhD project, we develop machine learning models for automatic analysis of medical data and explain the results using established techniques from the field of explainable artificial intelligence. Current research indicate that there are still open issues to be solved in order for end users to understand multimedia systems powered by machine learning. Consequently, new explanation techniques will also be developed. Different types of medical data are applied in order to investigate the generalizability of the methods.},
	isbn = {978-1-4503-9283-9/22/06},
	doi = {10.1145/3524273.3533925},
	author = {Stor{\r a}s, Andrea and Str{\"u}mke, Inga and Riegler, Michael and Halvorsen, P{\r a}l}
}
@misc {42696,
	title = {Explainable Artificial Intelligence in Medicine},
	howpublished = {Nordic AI Meet 2022},
	year = {2022},
	abstract = {Machine learning (ML) has shown outstanding abilities to solve a large variety of tasks such as image recognition and natural language processing, which has huge relevance for the medical field. Complex ML models, including convolutional neural networks (CNNs), are used to analyse high dimensional data such as images and videos from medical examinations.\&nbsp;With increasing model complexity, the demand for techniques improving human understanding of the ML models also increases. If medical doctors do not understand how the models work, they might not know when the models are actually wrong or even refuse to use them. This can hamper the implementation of ML systems in the clinic and negatively affect patients.\&nbsp;To promote successful integration of ML systems in the clinic, it is important to provide explanations that establish trust in the models among healthcare personnel.\&nbsp;Explainable artificial intelligence (XAI) aims to provide explanations about ML models and their predictions. Several techniques have already been developed.\&nbsp;Existing XAI methods often fail to meet the requirements of medical doctors, probably because they are not sufficiently involved in the development of the methods.\&nbsp;We develop ML models solving tasks in various medical domains. The resulting models are explained using a selection of existing XAI methods, and the explanations are evaluated by medical experts. Their feedback is used to develop improved XAI methods.\&nbsp;We have investigated established techniques for making ML systems more transparent in the fields of gastroenterology, assisted reproductive technology, organ transplantation and cardiology.\&nbsp;Experiences from our projects will be used to develop new explanation techniques for clinical practice in close collaboration with medical experts.},
	keywords = {Explainable artificial intelligence, Machine learning, medicine},
	author = {Stor{\r a}s, Andrea and Str{\"u}mke, Inga and Riegler, Michael and Halvorsen, P{\r a}l}
}
@article {42761,
	title = {Exploration of Different Time Series Models for Soccer Athlete Performance Prediction},
	journal = {MDPI Engineering Proceedings},
	volume = {18},
	year = {2022},
	pages = {37},
	publisher = {MDPI},
	doi = {10.3390/engproc2022018037},
	author = {Kulakou, Siarhei and Ragab, Nourhan and Midoglu, Cise and Boeker, Matthias and Johansen, Dag and Riegler, Michael and Halvorsen, P{\r a}l}
}
@article {39351,
	title = {FANet: A Feedback Attention Network for Improved Biomedical Image Segmentation},
	journal = {IEEE Transactions on Neural Networks and Learning Systems},
	year = {2022},
	month = {Jan-01-2022},
	pages = {1 - 14},
	publisher = { IEEE},
	abstract = {The increase of available large clinical and experimental datasets has contributed to a substantial amount of important contributions in the area of biomedical image analysis. Image segmentation, which is crucial for any quantitative analysis, has especially attracted attention. Recent hardware advancement has led to the success of deep learning approaches. However, although deep learning models are being trained on large datasets, existing methods do not use the information from different learning epochs effectively. In this work, we leverage the information of each training epoch to prune the prediction maps of the subsequent epochs. We propose a novel architecture called feedback attention network (FANet) that unifies the previous epoch mask with the feature map of the current training epoch. The previous epoch mask is then used to provide hard attention to the learned feature maps at different convolutional layers. The network also allows rectifying the predictions in an iterative fashion during the test time. We show that our proposed feedback attention model provides a substantial improvement on most segmentation metrics tested on seven publicly available biomedical imaging datasets demonstrating the effectiveness of FANet. The source code is available at https://github.com/nikhilroxtomar/FANet.},
	issn = {2162-237X},
	doi = {10.1109/TNNLS.2022.3159394},
	url = {https://ieeexplore.ieee.org/document/9741842},
	author = {Nikhil Kumar {Tomar} and Jha, Debesh and Riegler, Michael and H{\r a}vard D. {Johansen} and Johansen, Dag and Rittscher, Jens and Halvorsen, P{\r a}l and Ali, Sharib}
}
@misc {42697,
	title = {From a need, to an idea, to a complete system: a perspective based on real-world applications},
	howpublished = {IEEE/ACM International Symposium on Quality of Service (virtual)},
	year = {2022},
	month = {06/2022},
	publisher = {IEEE},
	type = {Keynote},
	abstract = {Researchers and developers have been talking about what determines a good system in various aspects for a long time, and eventually, it is all about quality. We are interested in quality throughout the entire holistic system, from data production to data consumption, and we have for several years aimed to solve real-world problems with a focus on both functional and non-functional requirements. This includes optimizing the various steps of both workflow and computing pipelines.In this talk, we will address quality at various levels and aspects within a holistic system. We will highlight some examples starting from challenges in society, using sports and health as showcases, via researching solutions where we optimize workflows, system performance and user experiences, to observations of real use and deployments of the systems. In particular, the talk will cover a video and metadata system for commercial sport production and dissemination as an integrated, next generation live streaming and archive system. We will also use an example from an AI-based medical computer assisted diagnosis system to detect anomalies during colonoscopy examinations. The talk will look at various solutions and the state of the art, and will conclude with various open challenges.},
	url = {https://iwqos2022.ieee-iwqos.org/program/keynote/},
	author = {Halvorsen, P{\r a}l}
}
@inproceedings {42441,
	title = {HOST-ATS: Automatic Thumbnail Selection with Dashboard-Controlled ML Pipeline and Dynamic User Survey},
	journal = {Proceedings of the 13th ACM Multimedia Systems Conference (MMSys {\textquoteright}22)},
	year = {2022},
	pages = {334-340},
	publisher = {ACM},
	doi = {10.1145/3524273.3532908},
	author = {Husa, Andreas and Midoglu, Cise and Hammou, Malek and Halvorsen, P{\r a}l and Riegler, Michael}
}
@inproceedings {42442,
	title = {Huldra: A Framework for Collecting Crowdsourced Feedback on Multimedia Assets},
	journal = {Proceedings of the 13th ACM Multimedia Systems Conference (MMSys {\textquoteright}22)},
	year = {2022},
	pages = {203-209},
	publisher = {ACM},
	doi = {10.1145/3524273.3532887},
	author = {Hammou, Malek and Midoglu, Cise and Hicks, Steven and Stor{\r a}s, Andrea and Saeed Shafiee {Sabet} and Str{\"u}mke, Inga and Riegler, Michael and Halvorsen, P{\r a}l}
}
@inproceedings {42711,
	title = {Human vs. GPT-3: The challenges of extracting emotions from child responses},
	journal = {The 14th International Conference on Quality of Multimedia Experience},
	year = {2022},
	publisher = { IEEE},
	isbn = {978-1-6654-8794-8},
	issn = {2472-7814},
	doi = {10.1109/QoMEX55416.2022.9900885},
	url = {https://ieeexplore.ieee.org/document/9900885},
	author = {Lammerse, Myrthe and Syed Zohaib {Hassan} and Saeed Shafiee {Sabet} and Riegler, Michael and Halvorsen, P{\r a}l}
}
@inproceedings {28231,
	title = {Investigative Interviews using a Multimodal Virtual Avatar},
	journal = {American Psychology-Law Society Conference 2022},
	year = {2022},
	publisher = {American Psychology-Law Society},
	address = {Denver USA,},
	abstract = {To meet best-practice standards, we are developing an interactive virtual avatar aiming as a training tool to raise interviewing skills of child-welfare and law-enforcement professionals. Therefore, we present the {\textquotedblleft}Ilma{\textquotedblright} avatar that recognizes interviewers{\textquoteright} behavior during open-ended, closed and leading questions, and which can automatically respond to the conversation. We conducted a user study in which master students (N=3) and child protective workers (N=8)\&nbsp; interviewed {\textquotedblleft}Ilma{\textquotedblright}\&nbsp; and rated their perception of the interaction. The results show that the participants valued the interaction and found the avatar useful. Thus, it has great potential to be an effective training tool.},
	author = {Gunn Astrid {Baugerud} and Powell, Martine and Riegler, Michael and Halvorsen, P{\r a}l and Michael E. {Lamb} and Saeed Shafiee {Sabet} and Syed Zohaib {Hassan} and Salehi, Pegah and Ragnhild K. {R{\o}ed} and Miriam S. {Johnson}}
}
@article {39342,
	title = {Meta-learning with implicit gradients in a few-shot setting for medical image segmentation},
	journal = {Computers in Biology and Medicine},
	volume = {143},
	year = {2022},
	month = {Jan-04-2022},
	pages = {105227},
	publisher = {Elsevier},
	abstract = {Widely used traditional supervised deep learning methods require a large number of training samples but often fail to generalize on unseen datasets. Therefore, a more general application of any trained model is quite limited for medical imaging for clinical practice. Using separately trained models for each unique lesion category or a unique patient population will require sufficiently large curated datasets, which is not practical to use in a real-world clinical set-up. Few-shot learning approaches can not only minimize the need for an enormous number of reliable ground truth labels that are labour-intensive and expensive, but can also be used to model on a dataset coming from a new population. To this end, we propose to exploit an optimization-based implicit model agnostic meta-learning (iMAML) algorithm under few-shot settings for medical image segmentation. Our approach can leverage the learned weights from diverse but small training samples to perform analysis on unseen datasets with high accuracy. We show that, unlike classical few-shot learning approaches, our method improves generalization capability. To our knowledge, this is the first work that exploits iMAML for medical image segmentation and explores the strength of the model on scenarios such as meta-training on unique and mixed instances of lesion datasets. Our quantitative results on publicly available skin and polyp datasets show that the proposed method outperforms the naive supervised baseline model and two recent few-shot segmentation approaches by large margins. In addition, our iMAML approach shows an improvement of 2\%{\textendash}4\% in dice score compared to its counterpart MAML for most experiments.},
	issn = {00104825},
	doi = {10.1016/j.compbiomed.2022.105227},
	url = {https://linkinghub.elsevier.com/retrieve/pii/S0010482522000191},
	author = {Khadka, Rabindra and Jha, Debesh and Hicks, Steven and Thambawita, Vajira and Riegler, Michael and Ali, Sharib and Halvorsen, P{\r a}l}
}
@misc {28442,
	title = {MMSys{\textquoteright}22 Grand Challenge on AI-based Video Production for Soccer},
	year = {2022},
	publisher = {arXiv},
	url = {https://arxiv.org/abs/2202.01031},
	author = {Midoglu, Cise and Hicks, Steven and Thambawita, Vajira and Kupka, Tomas and Halvorsen, P{\r a}l}
}
@inproceedings {42708,
	title = {Is More Realistic Better? A Comparison of Game Engine and GAN-based Avatars for Investigative Interviews of Children},
	journal = {ICDAR {\textquoteright}22: Proceedings of the 3rd ACM Workshop on Intelligent Cross-Data Analysis and Retrieval},
	year = {2022},
	pages = {41-49},
	publisher = {ACM},
	address = {New York, NY, USA},
	isbn = {9781450392419},
	doi = {10.1145/351273110.1145/3512731.3534209},
	url = {https://dl.acm.org/doi/proceedings/10.1145/3512731},
	author = {Salehi, Pegah and Syed Zohaib {Hassan} and Saeed Shafiee {Sabet} and Gunn Astrid {Baugerud} and Miriam Sinkerud {Johnson} and Halvorsen, P{\r a}l and Riegler, Michael},
	editor = {Dao, Minh-Son and Dang-Nguyen, Duc-Tien and Riegler, Michael}
}
@article {39305,
	title = {MSRF-Net: A Multi-Scale Residual Fusion Network for Biomedical Image Segmentation},
	journal = {IEEE Journal of Biomedical and Health Informatics},
	volume = {26},
	year = {2022},
	month = {12/2021},
	pages = {2252-2263},
	publisher = {IEEE},
	abstract = {Methods based on convolutional neural networks have improved the performance of biomedical image segmentation. However, most of these methods cannot efficiently segment objects of variable sizes and train on small and biased datasets, which are common for biomedical use cases. While methods exist that incorporate multi-scale fusion approaches to address the challenges arising with variable sizes, they usually use complex models that are more suitable for general semantic segmentation problems. In this paper, we propose a novel architecture called Multi-Scale Residual Fusion Network (MSRF-Net), which is specially designed for medical image segmentation. The proposed MSRF-Net is able to exchange multi-scale features of varying receptive fields using a Dual-Scale Dense Fusion (DSDF) block. Our DSDF block can exchange information rigorously across two different resolution scales, and our MSRF sub-network uses multiple DSDF blocks in sequence to perform multi-scale fusion. This allows the preservation of resolution, improved information flow and propagation of both high- and low-level features to obtain accurate segmentation maps. The proposed MSRF-Net allows to capture object variabilities and provides improved results on different biomedical datasets. Extensive experiments on MSRF-Net demonstrate that the proposed method outperforms the cutting edge medical image segmentation methods on four publicly available datasets. We achieve the Dice Coefficient (DSC) of 0.9217, 0.9420, and 0.9224, 0.8824 on Kvasir-SEG, CVC-ClinicDB, 2018 Data Science Bowl dataset, and ISIC-2018 skin lesion segmentation challenge dataset respectively. We further conducted generalizability tests that also achieved the highest DSC score with 0.7921 and 0.7575 on CVC-ClinicDB and Kvasir-SEG, respectively.\&nbsp;},
	issn = {2168-2194},
	doi = {10.1109/JBHI.2021.3138024},
	url = {https://ieeexplore.ieee.org/document/9662196},
	author = {Srivastava, Abhishek and Jha, Debesh and Chanda, Sukalpa and Pal, Umapada and Johansen, Havard and Johansen, Dag and Riegler, Michael and Ali, Sharib and Halvorsen, P{\r a}l}
}
@inproceedings {28322,
	title = {Multimedia streaming analytics: quo vadis?},
	journal = {MHV {\textquoteright}22: Mile-High Video Conference},
	year = {2022},
	pages = {62 - 69},
	publisher = {ACM},
	address = {Denver, Colorado, USA},
	isbn = {9781450392228},
	doi = {10.1145/3510450.3517321},
	url = {https://dl.acm.org/doi/10.1145/3510450.3517321},
	author = {Midoglu, Cise and Avelino, Mariana and Shri Hari {Gopalakrishnan} and Pham, Stefan and Halvorsen, P{\r a}l}
}
@inproceedings {42796,
	title = {Njord: a fishing trawler dataset},
	journal = {Proceedings of the 13th ACM Multimedia Systems Conference (MMSYS)},
	year = {2022},
	month = {08/2022},
	publisher = {ACM},
	address = {New York, NY, USA},
	abstract = {Fish is one of the main sources of food worldwide. The commercial fishing industry has a lot of different aspects to consider, ranging from sustainability to reporting. The complexity of the domain also attracts a lot of research from different fields like marine biology, fishery sciences, cybernetics, and computer science. In computer science, detection of fishing vessels via for example remote sensing and classification of fish from images or videos using machine learning or other analysis methods attracts growing attention. Surprisingly, little work has been done that considers what is happening on board the fishing vessels. On the deck of the boats, a lot of data and important information are generated with potential applications, such as automatic detection of accidents or automatic reporting of fish caught. This paper presents Njord, a fishing trawler dataset consisting of surveillance videos from a modern off-shore fishing trawler at sea. The main goal of this dataset is to show the potential and possibilities that analysis of such data can provide. In addition to the data, we provide a baseline analysis and discuss several possible research questions this dataset could help answer.},
	isbn = {9781450392839},
	doi = {10.1145/3524273.3532886},
	url = {https://dl.acm.org/doi/pdf/10.1145/3524273.3532886},
	author = {Tor-Arne Schmidt {Nordmo} and Aril Bernhard {Ovesen} and Bj{\o}rn Aslak {Juliussen} and Hicks, Steven and Thambawita, Vajira and H{\r a}vard Dagenborg {Johansen} and Halvorsen, P{\r a}l and Riegler, Michael and Johansen, Dag},
	editor = {Murray, Niall and Simon, Gwendal and Farias, Mylene and Viola, Irene and Montagud, Mario}
}
@inproceedings {nguyen2022parallel,
	title = {Parallel feature selection based on the trace ratio criterion},
	journal = {International Joint Conference on Neural Networks (IJCNN)},
	year = {2022},
	publisher = {IEEE},
	author = {Nguyen, Thu and Thanh Nhan {Phan} and Van Nhuong {Nguyen} and Thanh Binh {Nguyen} and Halvorsen, P{\r a}l and Riegler, Michael}
}
@inproceedings {42722,
	title = {PolypConnect: Image inpainting for generating realistic gastrointestinal tract images with polyps},
	journal = {IEEE 35th International Symposium on Computer-Based Medical Systems (CBMS)},
	year = {2022},
	month = {07/2022},
	pages = {66-71},
	publisher = {IEEE},
	abstract = {Early identification of a polyp in the lower gastrointestinal (GI) tract can lead to prevention of life-threatening colorectal cancer. Developing computer-aided diagnosis (CAD) systems to detect polyps can improve detection accuracy and efficiency and save the time of the domain experts called endoscopists. Lack of annotated data is a common challenge when building CAD systems. Generating synthetic medical data is an active research area to overcome the problem of having relatively few true positive cases in the medical domain. To be able to efficiently train machine learning (ML) models, which are the core of CAD systems, a considerable amount of data should be used. In this respect, we propose the PolypConnect pipeline, which can convert non-polyp images into polyp images to increase the size of training datasets for training. We present the whole pipeline with quantitative and qualitative evaluations involving endoscopists. The polyp segmentation model trained using synthetic data, and real data shows a 5.1\% improvement of mean intersection over union (mIOU), compared to the model trained only using real data. The codes of all the experiments are available on GitHub to reproduce the results.},
	doi = {10.1109/CBMS55023.2022.00019},
	author = {Jan Andre {Fageren} and Thambawita, Vajira and Stor{\r a}s, Andrea and Parasa, Sravanthi and de Lange, Thomas and Halvorsen, P{\r a}l and Riegler, Michael}
}
@misc {42540,
	title = {Predicting drug exposure in kidney transplanted patients using machine learning},
	year = {2022},
	type = {Poster presentation},
	address = {NORA Annual Conference, Stavanger, Norway},
	author = {Stor{\r a}s, Andrea and Riegler, Michael and Halvorsen, P{\r a}l and {\r A}sberg, Anders and Str{\"u}mke, Inga}
}
@inproceedings {42542,
	title = {Predicting Tacrolimus Exposure in Kidney Transplanted Patients Using Machine Learning},
	journal = {35th IEEE CBMS International Symposium on Computer-Based Medical Systems},
	year = {2022},
	pages = {38-43},
	publisher = { IEEE},
	abstract = {Tacrolimus is one of the cornerstone immunosuppressive drugs in most transplantation centers worldwide following solid organ transplantation. Therapeutic drug monitoring of tacrolimus is necessary in order to avoid rejection of the transplanted organ or severe side effects. However, finding the right dose for a given patient is challenging, even for experienced clinicians. Consequently, a tool that can accurately estimate the drug exposure for individual dose adaptions would be of high clinical value. In this work, we propose a new technique using machine learning to estimate the tacrolimus exposure in kidney transplant recipients. Our models achieve predictive errors that are at the same level as an established population pharmacokinetic model, but are faster to develop and require less knowledge about the pharmacokinetic properties of the drug.},
	keywords = {Machine learning, personalized medicine, transplantation},
	doi = {10.1109/CBMS55023.2022.00014},
	author = {Stor{\r a}s, Andrea and {\r A}sberg, Anders and Halvorsen, P{\r a}l and Riegler, Michael and Str{\"u}mke, Inga}
}
@article {42713,
	title = {Prediction of Schizophrenia from Activity Data using Hidden Markov Model Parameters},
	journal = {Neural Computing and Applications},
	year = {2022},
	publisher = { Springer},
	author = {Boeker, Matthias and Riegler, Michael and Hugo Lewi {Hammer} and Jakobsen, Petter and Halvorsen, P{\r a}l}
}
@article {42720,
	title = {Real-time deep learning based multi object tracking of spermatozoa in fresh samples},
	journal = {Human Reproduction},
	volume = {37},
	year = {2022},
	month = {06/2022},
	publisher = {Oxford University Press},
	doi = {https://doi.org/10.1093/humrep/deac107.104},
	author = {Thambawita, Vajira and Hicks, Steven and Stor{\r a}s, Andrea and Witczak, Oliwia and Jorunn M. {Andersen} and Hugo Lewi {Hammer} and Halvorsen, P{\r a}l and Riegler, Michael and Haugen B. {Trine}}
}
@inproceedings {torpmann2022segmentation,
	title = {Segmentation Consistency Training: Out-of-Distribution Generalization for Medical Image Segmentation},
	journal = {2022 IEEE International Symposium on Multimedia (ISM)},
	year = {2022},
	pages = {42-49},
	publisher = {IEEE},
	doi = {10.1109/ISM55400.2022.00012},
	author = {Torpmann-Hagen, Birk and Thambawita, Vajira and Glette, Kyrre and Halvorsen, P{\r a}l and Riegler, Michael}
}
@article {42539,
	title = {SinGAN-Seg: Synthetic training data generation for medical image segmentation},
	journal = {PLOS ONE},
	volume = {17},
	year = {2022},
	month = {05/2022},
	pages = {e0267976},
	publisher = {PLOS},
	abstract = {Analyzing medical data to find abnormalities is a time-consuming and costly task, particularly for rare abnormalities, requiring tremendous efforts from medical experts. Therefore, artificial intelligence has become a popular tool for the automatic processing of medical data, acting as a supportive tool for doctors. However, the machine learning models used to build these tools are highly dependent on the data used to train them. Large amounts of data can be difficult to obtain in medicine due to privacy reasons, expensive and time-consuming annotations, and a general lack of data samples for infrequent lesions. In this study, we present a novel synthetic data generation pipeline, called\&nbsp;SinGAN-Seg, to produce synthetic medical images with corresponding masks using a single training image. Our method is different from the traditional generative adversarial networks (GANs) because our model needs only a single image and the corresponding ground truth to train. We also show that the synthetic data generation pipeline can be used to produce alternative artificial segmentation datasets with corresponding ground truth masks when real datasets are not allowed to share. The pipeline is evaluated using qualitative and quantitative comparisons between real data and synthetic data to show that the style transfer technique used in our pipeline significantly improves the quality of the generated data and our method is better than other state-of-the-art GANs to prepare synthetic images when the size of training datasets are limited. By training UNet++ using both real data and the synthetic data generated from the SinGAN-Seg pipeline, we show that the models trained on synthetic data have very close performances to those trained on real data when both datasets have a considerable amount of training data. In contrast, we show that synthetic data generated from the SinGAN-Seg pipeline improves the performance of segmentation models when training datasets do not have a considerable amount of data. All experiments were performed using an open dataset and the code is publicly available on GitHub.},
	doi = {https://doi.org/10.1371/journal.pone.0267976},
	url = {https://doi.org/10.1371/journal.pone.0267976},
	author = {Thambawita, Vajira and Salehi, Pegah and Sajad Amouei {Sheshkal} and Hicks, Steven and Hugo Lewi {Hammer} and Parasa, Sravanthi and de Lange, Thomas and Halvorsen, P{\r a}l and Riegler, Michael}
}
@inbook {42536,
	title = {Smittestopp analytics: Analysis of position data},
	booktitle = { Smittestopp - A Case Study on Digital Contact Tracing},
	volume = {11},
	year = {2022},
	month = {06/2022},
	pages = {63 - 79},
	publisher = {Springer International Publishing},
	organization = {Springer International Publishing},
	address = {Cham},
	abstract = {Contact tracing applications generally rely on Bluetooth data. This type of data works well to determine whether a contact occurred (smartphones were close to each other) but cannot offer the contextual information GPS data can offer. Did the contact happen on a bus? In a building? And of which type? Are some places recurrent contact locations? By answering such questions, GPS data can help develop more accurate and better-informed contact tracing applications. This chapter describes the ideas and approaches implemented for GPS data within the Smittestopp contact tracing application.We will present the pipeline used and the contribution of GPS data for contextual information, using inferred transport modes and surrounding POIs, showcasing the opportunities in the use of GPS information. Finally,we discuss ethical and privacy considerations, as well as some lessons learned.},
	isbn = {978-3-031-05465-5},
	issn = {2512-1677},
	doi = {10.1007/978-3-031-05466-2_4},
	url = {https://link.springer.com/content/pdf/10.1007/978-3-031-05466-2_4},
	author = {Thambawita, Vajira and Hicks, Steven and Jaouen, Ewan and Halvorsen, P{\r a}l and Riegler, Michael},
	editor = {Elmokashfi, Ahmed and Lysne, Olav and Naumova, Valeriya}
}
@inbook {42537,
	title = {Smittestopp Backend},
	booktitle = { Smittestopp - A Case Study on Digital Contact Tracing},
	volume = {11},
	year = {2022},
	month = {06/2022},
	pages = {29 - 62},
	publisher = {Springer International Publishing},
	organization = {Springer International Publishing},
	address = {Cham},
	abstract = {An efficient backend solution is of great importance for any large-scale system, and Smittestopp is no exception. The Smittestopp backend comprises various components for user and device registration, mobile app data ingestion, database and cloud operations, and web interface support. This chapter describes our journey from a vague idea to a deployed system. We provide an overview of the system internals and design iterations and discuss the challenges that we faced during the development process, along with the lessons learned. The Smittestopp backend handled around 1.5 million registered devices and provided various insights and analyses before being discontinued a few months after its launch.},
	isbn = {978-3-031-05465-5},
	issn = {2512-1677},
	doi = {10.1007/978-3-031-05466-2_3},
	url = {https://link.springer.com/content/pdf/10.1007/978-3-031-05466-2.pdf},
	author = {Midoglu, Cise and Ragan-Kelley, Benjamin and Reinemo, Sven-Arne and Jahren, Jon and Halvorsen, P{\r a}l},
	editor = {Elmokashfi, Ahmed and Lysne, Olav and Naumova, Valeriya}
}
@misc {42444,
	title = {Soccer Athlete Performance Prediction using Time Series Analysis},
	howpublished = {NORA Annual Conference},
	year = {2022},
	author = {Ragab, Nourhan and Midoglu, Cise and Halvorsen, P{\r a}l}
}
@inproceedings {42762,
	title = {Soccer Game Summarization using Audio Commentary, Metadata, and Captions},
	journal = {NarSUM {\textquoteright}22: Proceedings of the 1st Workshop on User-centric Narrative Summarization of Long Videos},
	year = {2022},
	pages = {13-22},
	publisher = {ACM},
	address = {New York, NY, USA},
	isbn = {9781450394932},
	doi = {10.1145/3552463.3557019},
	url = {https://doi.org/10.1145/3552463.3557019},
	author = {Gautam, Sushant and Midoglu, Cise and Saeed Shafiee {Sabet} and Dinesh Baniya {Kshatri} and Halvorsen, P{\r a}l}
}
@article {42991,
	title = {Synthesizing a Talking Child Avatar to Train Interviewers Working with Maltreated Children},
	journal = {Big Data and Cognitive Computing},
	volume = {6},
	year = {2022},
	month = {Jan-06-2022},
	pages = {62},
	publisher = {MDPI},
	doi = {10.3390/bdcc6020062},
	url = {https://www.mdpi.com/2504-2289/6/2/62https://www.mdpi.com/2504-2289/6/2/62/pdf},
	author = {Salehi, Pegah and Syed Zohaib {Hassan} and Lammerse, Myrthe and Saeed Shafiee {Sabet} and Riiser, Ingvild and Ragnhild Klingenber {R{\o}ed} and Miriam S. {Johnson} and Thambawita, Vajira and Hicks, Steven and Powell, Martine and Michael E. {Lamb} and Gunn Astrid {Baugerud} and Halvorsen, P{\r a}l and Riegler, Michael}
}
@inproceedings {42595,
	title = {Towards an AI-driven talking avatar in virtual reality for investigative interviews of children},
	journal = {GameSys {\textquoteright}22: Proceedings of the 2nd Workshop on Games Systems},
	year = {2022},
	pages = {9-15},
	publisher = {ACM},
	address = {New York, NY, USA},
	isbn = {9781450393812},
	doi = {10.1145/353408510.1145/3534085.3534340},
	url = {https://dl.acm.org/doi/10.1145/3534085.3534340},
	author = {Syed Zohaib {Hassan} and Salehi, Pegah and Ragnhild Klingenber {R{\o}ed} and Halvorsen, P{\r a}l and Gunn Astrid {Baugerud} and Miriam Sinkerud {Johnson} and Lison, Pierre and Riegler, Michael and Michael E. {Lamb} and Griwodz, Carsten and Saeed Shafiee {Sabet}},
	editor = {Claypool, Mark and Eg, Ragnhild}
}
@article {42795,
	title = {Towards the Neuroevolution of Low-level artificial general intelligence},
	journal = {Frontiers in Robotics and AI},
	volume = {9},
	year = {2022},
	month = {10/2022},
	publisher = {Frontiers},
	abstract = {In this work, we argue that the search for Artificial General Intelligence should start from a much lower level than human-level intelligence. The circumstances of intelligent behavior in nature resulted from an organism interacting with its surrounding environment, which could change over time and exert pressure on the organism to allow for learning of new behaviors or environment models. Our hypothesis is that learning occurs through interpreting sensory feedback when an agent acts in an environment. For that to happen, a body and a reactive environment are needed. We evaluate a method to evolve a biologically- inspired artificial neural network that learns from environment reactions named Neuroevolution of Artificial General Intelligence, a framework for low-level artificial general intelligence. This method allows the evolutionary complexification of a randomly-initialized spiking neural network with adaptive synapses, which controls agents instantiated in mutable environments. Such a configuration allows us to benchmark the adaptivity and generality of the controllers. The chosen tasks in the mutable environments are food foraging, emulation of logic gates, and cart-pole balancing. The three tasks are successfully solved with rather small network topologies and therefore it opens up the possibility of experimenting with more complex tasks and scenarios where curriculum learning is beneficial.},
	doi = {10.3389/frobt.2022.1007547},
	url = {https://www.frontiersin.org/articles/10.3389/frobt.2022.1007547/full},
	author = {Pontes-Filho, Sidney and Olsen, Kristoffer and Yazidi, Anis and Riegler, Michael and Halvorsen, P{\r a}l and Nichele, Stefano}
}
@inproceedings {42695,
	title = {Video Analytics in Elite Soccer: A Distributed Computing Perspective},
	journal = {IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM)},
	year = {2022},
	month = {06/2022},
	pages = {221-225},
	publisher = {IEEE},
	address = {Trondheim, Norway},
	abstract = {Ubiquitous sensors and Internet of Things (IoT) technologies have revolutionized the sports industry, providing new methodologies for planning, effective coordination of training, and match analysis post game. New methods, including machine learning, image and video processing, have been developed for performance evaluation, allowing the analyst to track the performance of a player in real-time. Following FIFA{\textquoteright}s 2015 approval of electronics performance and tracking system during games, performance data of a single player or the entire team is allowed to be collected using GPS-based wearables. Data from practice sessions outside the sporting arena is being collected in greater numbers than ever before. Realizing the significance of data in professional soccer, this paper presents video analytics, examines recent state-of-the-art literature in elite soccer, and summarizes existing real-time video analytics algorithms. We also discuss real-time crowdsourcing of the obtained data, tactical and technical performance, distributed computing and its importance in video analytics and propose a future research perspective.\&nbsp;},
	keywords = {analytics, football, soccer, Video},
	doi = {10.1109/SAM53842.2022.9827827},
	url = {https://ieeexplore.ieee.org/document/9827827},
	author = {Jha, Debesh and Rauniyar, Ashish and H{\r a}vard D. {Johansen} and Johansen, Dag and Riegler, Michael and Halvorsen, P{\r a}l and Bagci, Ulas}
}
@inproceedings {42710,
	title = {Virtual Reality Talking Avatar for Investigative Interviews of Maltreat Children},
	journal = {19th International Conference on Content-based Multimedia Indexing},
	year = {2022},
	pages = {201-204},
	publisher = {Association for Computing Machinery (ACM)},
	address = {New York, NY, USA},
	isbn = {9781450397209},
	doi = {10.1145/3549555.3549572},
	url = {https://doi.org/10.1145/3549555.3549572},
	author = {Syed Zohaib {Hassan} and Salehi, Pegah and Riegler, Michael and Miriam Sinkerud {Johnson} and Gunn Astrid {Baugerud} and Halvorsen, P{\r a}l and Saeed Shafiee {Sabet}}
}
@misc {42764,
	title = {Visual explanations for polyp detection: How medical doctors assess intrinsic versus extrinsic explanations},
	year = {2022},
	publisher = {arXiv},
	doi = {10.48550/arXiv.2204.00617},
	url = {https://arxiv.org/abs/2204.00617},
	author = {Hicks, Steven and Stor{\r a}s, Andrea and Riegler, Michael and Midoglu, Cise and Hammou, Malek and de Lange, Thomas and Parasa, Sravanthi and Halvorsen, P{\r a}l and Str{\"u}mke, Inga}
}
@article {28311,
	title = {Visual Sentiment Analysis from Disaster Images in Social Media},
	journal = {Sensors},
	volume = {22},
	number = {10},
	year = {2022},
	month = {05/2022},
	pages = {3628},
	publisher = {MDPI},
	abstract = {The increasing popularity of social networks and users{\textquoteright} tendency towards sharing their feelings, expressions, and opinions in text, visual, and audio content have opened new opportunities and challenges in sentiment analysis. While sentiment analysis of text streams has been widely explored in the literature, sentiment analysis from images and videos is relatively new. This article focuses on visual sentiment analysis in a societally important domain, namely disaster analysis in social media. To this aim, we propose a deep visual sentiment analyzer for disaster-related images, covering different aspects of visual sentiment analysis starting from data collection, annotation, model selection, implementation, and evaluations. For data annotation and analyzing people{\textquoteright}s sentiments towards natural disasters and associated images in social media, a crowd-sourcing study has been conducted with a large number of participants worldwide. The crowd-sourcing study resulted in a large-scale benchmark dataset with four different sets of annotations, each aiming at a separate task. The presented analysis and the associated dataset, which is made public, will provide a baseline/benchmark for future research in the domain. We believe the proposed system can contribute toward more livable communities by helping different stakeholders, such as news broadcasters, humanitarian organizations, as well as the general public.},
	doi = {10.3390/s22103628},
	url = {https://doi.org/10.3390/s22103628},
	author = {Syed Zohaib {Hassan} and Ahmad, Kashif and Hicks, Steven and Halvorsen, P{\r a}l and Al-Fuqaha, Ala and Conci, Nicola and Riegler, Michael}
}
@inproceedings {42712,
	title = {When Every Millisecond Counts: The Impact of Delay in VR Gaming},
	journal = {The 14th International Conference on Quality of Multimedia Experience},
	year = {2022},
	publisher = {IEEE},
	doi = {10.1109/QoMEX55416.2022.9900908},
	url = {https://ieeexplore.ieee.org/document/9900908},
	author = {Saeed Shafiee {Sabet} and Eg, Ragnhild and Raaen, Kjetil and Qasim, Muhammed and Riegler, Michael and Halvorsen, P{\r a}l}
}
@article {28313,
	title = {AI-Based Video Clipping of Soccer Events},
	journal = {Machine Learning and Knowledge Extraction},
	volume = {3},
	year = {2021},
	month = {12/2021},
	pages = {990 - 1008},
	publisher = {MDPI},
	abstract = {The current gold standard for extracting highlight clips from soccer games is the use of manual annotations and clippings, where human operators define the start and end of an event and trim away the unwanted scenes. This is a tedious, time-consuming, and expensive task, to the extent of being rendered infeasible for use in lower league games. In this paper, we aim to automate the process of highlight generation using logo transition detection, scene boundary detection, and optional scene removal. We experiment with various approaches, using different neural network architectures on different datasets, and present two models that automatically find the appropriate time interval for extracting goal events. These models are evaluated both quantitatively and qualitatively, and the results show that we can detect logo and scene transitions with high accuracy and generate highlight clips that are highly acceptable for viewers. We conclude that there is considerable potential in automating the overall soccer video clipping process.\&nbsp;\&nbsp;},
	doi = {10.3390/make3040049},
	url = {https://www.mdpi.com/2504-4990/3/4/49/pdf},
	author = {Joakim Olav {Valand} and Kadragic, Haris and Hicks, Steven and Thambawita, Vajira and Midoglu, Cise and Kupka, Tomas and Johansen, Dag and Riegler, Michael and Halvorsen, P{\r a}l}
}
@inbook {28006,
	title = {Artificial Intelligence in Gastroenterology},
	booktitle = {Artificial Intelligence in Medicine},
	year = {2021},
	month = {09/2021},
	pages = {1 - 20},
	publisher = {Springer International Publishing},
	organization = {Springer International Publishing},
	address = {Cham},
	abstract = {The holy grail in endoscopy examinations has for a long time been assisted diagnosis using Artificial Intelligence (AI). Recent developments in computer hardware are now enabling technology to equip clinicians with promising tools for computer-assisted diagnosis (CAD) systems. However, creating viable models or architectures, training them, and assessing their ability to diagnose at a human level, are complicated tasks. This is currently an active area of research, and many promising methods have been proposed. In this chapter, we give an overview of the topic. This includes a description of current medical challenges followed by a description of the most commonly used methods in the field. We also present example results from research targeting some of these challenges, and a discussion on open issues and ongoing work is provided. Hopefully, this will inspire and enable readers to future develop CAD systems for gastroenterology.},
	keywords = {Anomaly detection, artificial intelligence, Gastrointestinal endoscopy, Hand-crafted features, Neural Networks, Performance, Semantic segmentation},
	isbn = {978-3-030-58080-3},
	doi = {10.1007/978-3-030-58080-3_163-2},
	url = {https://link.springer.com/referenceworkentry/10.1007\%2F978-3-030-58080-3_163-2},
	author = {Str{\"u}mke, Inga and Hicks, Steven and Thambawita, Vajira and Jha, Debesh and Parasa, Sravanthi and Riegler, Michael and Halvorsen, P{\r a}l},
	editor = {Lidstr{\"o}mer, Niklas and Ashrafian, Hutan}
}
@article {28137,
	title = {Artificial intelligence in the fertility clinic: status, pitfalls and possibilities},
	journal = {Human Reproduction},
	volume = {36},
	year = {2021},
	month = {07/2021},
	pages = {2429 - 2442},
	publisher = {Oxford Academic},
	abstract = {In recent years, the amount of data produced in the field of ART has increased exponentially. The diversity of data is large, ranging from videos to tabular data. At the same time, artificial intelligence (AI) is progressively used in medical practice and may become a promising tool to improve success rates with ART. AI models may compensate for the lack of objectivity in several critical procedures in fertility clinics, especially embryo and sperm assessments. Various models have been developed, and even though several of them show promising performance, there are still many challenges to overcome. In this review, we present recent research on AI in the context of ART. We discuss the strengths and weaknesses of the presented methods, especially regarding clinical relevance. We also address the pitfalls hampering successful use of AI in the clinic and discuss future possibilities and important aspects to make AI truly useful for ART.},
	issn = {0268-1161},
	doi = {10.1093/humrep/deab168},
	url = {https://academic.oup.com/humrep/article/36/9/2429/6330662},
	author = {Riegler, Michael and M H {Stensen} and Witczak, O and J M {Andersen} and Hicks, Steven and Hugo Lewi {Hammer} and Delbarre, E and Halvorsen, P{\r a}l and Yazidi, A and Holst, N and T B {Haugen}}
}
@inproceedings {28315,
	title = {Automated Clipping of Soccer Events using Machine Learning},
	journal = {IEEE International Symphosium of Multimedia (ISM)},
	year = {2021},
	month = {12/2021},
	publisher = { IEEE},
	doi = {10.1109/ISM52913.2021.00042},
	author = {Valand, Joakim and Kadragic, Haris and Hicks, Steven and Thambawita, Vajira and Midoglu, Cise and Kupka, Tomas and Johansen, Dag and Riegler, Michael and Halvorsen, P{\r a}l}
}
@article {28314,
	title = {Automated Event Detection and Classification in Soccer: The Potential of Using Multiple Modalities},
	journal = {Machine Learning and Knowledge Extraction},
	volume = {3},
	year = {2021},
	month = {12/2021},
	pages = {1030 - 1054},
	publisher = {MDPI},
	abstract = {Detecting events in videos is a complex task, and many different approaches, aimed at a large variety of use-cases, have been proposed in the literature. Most approaches, however, are unimodal and only consider the visual information in the videos. This paper presents and evaluates different approaches based on neural networks where we combine visual features with audio features to detect (spot) and classify events in soccer videos. We employ model fusion to combine different modalities such as video and audio, and test these combinations against different state-of-the-art models on the SoccerNet dataset. The results show that a multimodal approach is beneficial. We also analyze how the tolerance for delays in classification and spotting time, and the tolerance for prediction accuracy, influence the results. Our experiments show that using multiple modalities improves event detection performance for certain types of events.},
	doi = {10.3390/make3040051},
	url = {https://www.mdpi.com/2504-4990/3/4/51/pdf},
	author = {Olav Andre Nerg {Rongved} and Stige, Markus and Hicks, Steven and Thambawita, Vajira and Midoglu, Cise and Zouganeli, Evi and Johansen, Dag and Riegler, Michael and Halvorsen, P{\r a}l}
}
@article {27774,
	title = {A comprehensive analysis of classification methods in gastrointestinal endoscopy imaging},
	journal = {Medical Image Analysis},
	volume = {70},
	year = {2021},
	pages = {102007},
	publisher = {Elsevier},
	abstract = {Gastrointestinal endoscopy has\&nbsp;been\&nbsp;an\&nbsp;active field\&nbsp;of research motivated by the large number of highly lethal GI cancers. Early GI cancer precursors are often missed during the endoscopic surveillance. \&nbsp; The high missed rate of such abnormalities during endoscopy is thus a\&nbsp; critical bottleneck. Lack of attentiveness due to tiring procedures, and requirement of training are few contributing factors. An automatic\&nbsp; GI\&nbsp; disease classification system can help reduce such risks by flagging suspicious frames and lesions. GI endoscopy consists of several multi-organ surveillance, therefore, there is need to develop methods that can generalize to various endoscopic findings. In this realm, we present a comprehensive analysis of the\&nbsp; Medico\&nbsp; GI\&nbsp; challenges:\&nbsp; Medical\&nbsp; Multimedia Task at MediaEval 2017, Medico Multimedia Task at MediaEval 2018,\&nbsp; and\&nbsp; BioMedia\&nbsp; ACM\&nbsp; MM\&nbsp; Grand\&nbsp; Challenge\&nbsp; 2019.\&nbsp; These challenges are initiative to set-up\&nbsp; a\&nbsp; benchmark for different computer vision methods applied to the multi-class endoscopic images and promote to build new approaches that could reliably be used in clinics. We report the performance of 21 participating teams over a\&nbsp; period of three consecutive years and provide a\&nbsp; detailed analysis of the methods used by the participants, highlighting the challenges and shortcomings of the current approaches and dissect their credibility for the use in clinical settings.\&nbsp; Our analysis revealed that the participants achieved an improvement on maximum\&nbsp; Mathew correlation coefficient\&nbsp; (MCC)\&nbsp; from\&nbsp; 82.68\%\&nbsp; in\&nbsp; 2017\&nbsp; to\&nbsp; 93.98\%\&nbsp; in\&nbsp; 2018\&nbsp; and 95.20\% in 2019 challenges, and a significant increase in computational speed over consecutive years.},
	keywords = {Artificial intelligence, BioMedia 2019 Grand Challenge, Computer-aided detection and diagnosis, Gastrointestinal endoscopy challenges, Medical imaging, Medico Task 2017, Medico Task 2018},
	doi = {https://doi.org/10.1016/j.media.2021.102007},
	author = {Jha, Debesh and Ali, Sharib and Hicks, Steven and Thambawita, Vajira and Borgli, Hanna and Pia H. {Smedsrud} and de Lange, Thomas and Pogorelov, Konstantin and Wang, Xiaowei and Harzig, Philipp and Tran, Minh-Triet and Meng, Wenhua and Hoang, Trung-Hieu and Dias, Danielle and Tobey H. {Ko} and Agrawal, Taruna and Ostroukhova, Olga and Khan, Zeshan and Muhammad Atif {Tahir} and Liu, Yang and Chang, Yuan and Kirker{\o}d, Mathias and Johansen, Dag and Lux, Mathias and H{\r a}vard D. {Johansen} and Riegler, Michael and Halvorsen, P{\r a}l}
}
@article {27640,
	title = {A Comprehensive Study on Colorectal Polyp Segmentation with ResUNet++, Conditional Random Field and Test-Time Augmentation},
	journal = {IEEE Journal of Biomedical and Health Informatics},
	volume = {25},
	year = {2021},
	pages = {2029 - 2040},
	publisher = { IEEE},
	abstract = {Colonoscopy is considered the gold standard for detection of colorectal cancer and its precursors. Existing examination methods are, however, hampered by high overall miss-rate, and many abnormalities are left undetected. Computer-Aided Diagnosis systems based on advanced machine learning algorithms are touted as a game-changer that can identify regions in the colon overlooked by the physicians during endoscopic examinations, and help detect and characterize lesions. In previous work, we have proposed the ResUNet++ architecture and demonstrated that it produces more efficient results compared with its counterparts U-Net and ResUNet. In this paper, we demonstrate that further improvements to the overall prediction performance of the ResUNet++ architecture can be achieved by using Conditional Random Field (CRF) and Test-Time Augmentation (TTA). We have performed extensive evaluations and validated the improvements using six publicly available datasets: Kvasir-SEG, CVC-ClinicDB, CVC-ColonDB, ETIS-Larib PolypDB, ASU-Mayo Clinic Colonoscopy Video Database, and CVC-VideoClinicDB. Moreover, we compare our proposed architecture and resulting model with other State-of-the-art methods. To explore the generalization capability of ResUNet++ on different publicly available polyp datasets, so that it could be used in a real-world setting, we performed an extensive cross-dataset evaluation. The experimental results show that applying CRF andTTA improves the performance on various polyp segmentation datasets both on the same dataset and cross-dataset. To check the model{\textquoteright}s performance on difficult to detect polyps, we selected, with the help of an expert gastroenterologist,196sessile or flat polyps that are less than ten millimeters in size. This additional data has been made available as a subset of Kvasir-SEG. Our approaches showed good results for flat or sessile and smaller polyps, which are known to be one of the major reasons for high polyp miss-rates. This is one of the significant strengths of our work and indicates that our methods should be investigated further for use in clinical practice.},
	keywords = {colonoscopy, conditional random field, generalization, Polyp segmentation, ResUNet++, test-time augmentation},
	doi = {10.1109/JBHI.2021.3049304},
	author = {Jha, Debesh and Pia H. {Smedsrud} and Johansen, Dag and de Lange, Thomas and H{\r a}vard D. {Johansen} and Halvorsen, P{\r a}l and Riegler, Michael}
}
@inproceedings {27831,
	title = {Data Augmentation Using Generative Adversarial Networks For Creating Realistic Artificial Colon Polyp Images},
	journal = {DDW 2021},
	year = {2021},
	author = {Thambawita, Vajira and Str{\"u}mke, Inga and Hicks, Steven and Riegler, Michael and Halvorsen, P{\r a}l and Parasa, Sravanthi}
}
@inproceedings {27635,
	title = {DDANet: Dual Decoder Attention Network for Automatic Polyp Segmentation},
	journal = {25th International Conference on Pattern Recognition},
	year = {2021},
	pages = {307-314},
	publisher = { Springer},
	abstract = {Colonoscopy is the gold standard for examination and detection of colorectal polyps. Localization and delineation of polyps can play a vital role in treatment (e.g., surgical planning) and prognostic decision making. Polyp segmentation can provide detailed boundary information for clinical analysis. Convolutional neural networks have improved the performance in colonoscopy. However, polyps usually possess various challenges, such as intra-and inter-class variation and noise. While manual labeling for polyp assessment requires time from experts and is prone to human error (e.g., missed lesions), an automated, accurate, and fast segmentation can improve the quality of delineated lesion boundaries and reduce missed rate. The Endotect challenge provides an opportunity to benchmark computer vision methods by training on the publicly available Hyperkvasir and testing on a separate unseen dataset. In this paper, we propose a novel architecture called {\textquoteleft}{\textquoteleft}DDANet{\textquoteright}{\textquoteright} based on a dual decoder attention network. Our experiments demonstrate that the model trained on the Kvasir-SEG dataset and tested on an unseen dataset achieves a dice coefficient of 0.7874, mIoU of 0.7010, recall of 0.7987, and a precision of 0.8577, demonstrating the generalization ability of our model.},
	keywords = {Benchmarking, Convolutional neural network, deep learning, Polyp segmentation},
	author = {Nikhil Kumar {Tomar} and Jha, Debesh and Ali, Sharib and H{\r a}vard D. {Johansen} and Johansen, Dag and Riegler, Michael and Halvorsen, P{\r a}l}
}
@article {kanters2021deep,
	title = {Deep learning neural network can measure ECG intervals and amplitudes accurately},
	journal = {Journal of Electrocardiology},
	volume = {69},
	year = {2021},
	pages = {82},
	publisher = {Elsevier},
	author = {Jorgen K {Kanters} and Hicks, Steven and Jonas L {Isaksen} and Grarup, Niels and Niels-Henrik Holstein {Rathlou} and Ghouse, Jonas and Ahlberg, Gustav and Morten Salling {Olesen} and Linneberg, Allan and Ellervik, Christina and Halvorsen, P{\r a}l and Riegler, Michael}
}
@article {Thambawita2021.04.27.21256189,
	title = {DeepFake electrocardiograms: the key for open science for artificial intelligence in medicine},
	journal = {Scientific Reports},
	year = {2021},
	publisher = {Nature Publishing Group},
	abstract = {Recent global developments underscore the prominent role big data have in modern medical science. Privacy issues are a prevalent problem for collecting and sharing data between researchers. Synthetic data generated to represent real data carrying similar information and distribution may alleviate the privacy issue.In this study, we present generative adversarial networks (GANs) capable of generating realistic synthetic DeepFake 12-lead 10-sec electrocardiograms (ECGs). We have developed and compare two methods, WaveGAN* and Pulse2Pulse GAN. We trained the GANs with 7,233 real normal ECG to produce 121,977 DeepFake normal ECGs. By verifying the ECGs using a commercial ECG interpretation program (MUSE 12SL, GE Healthcare), we demonstrate that the Pulse2Pulse GAN was superior to the WaveGAN to produce realistic ECGs. ECG intervals and amplitudes were similar between the DeepFake and real ECGs. These synthetic ECGs are fully anonymous and cannot be referred to any individual, hence they may be used freely. The synthetic dataset will be available as open access for researchers at OSF.io and the DeepFake generator available at the Python Package Index (PyPI) for generating synthetic ECGs.In conclusion, we were able to generate realistic synthetic ECGs using adversarial neural networks on normal ECGs from two population studies, i.e., there by addressing the relevant privacy issues in medical datasets.Competing Interest StatementThe authors have declared no competing interest.Clinical TrialN/AFunding StatementThis work is funded in part by Novo Nordisk Foundation project number NNF18CC0034900.Author DeclarationsI confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.YesThe details of the IRB/oversight body that provided approval or exemption for the research described are given below:We confirm that all experiments were performed in accordance with Helsinki guidelines and regulations of the Danish Regional Committees for Medical and Health Research Ethics. The data studies were approved by the ethical committee of Region Zealand (SJ-113, SJ-114, SJ-191), ethical committee of Copenhagen Amt (KA 98 155).All necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived.YesI understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).YesI have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable.YesThe Normal DeepFake ECGs are available at OSF (https://osf.io/6hved/) with corresponding MUSE 12SL ground truth values freely downloadable and usable for ECG algorithm development. The DeepFake generative model is available at https://pypi.org/project/deepfake-ecg/ to generate only synthetic ECGs. https://osf.io/6hved/ https://pypi.org/project/deepfake-ecg/},
	doi = {10.1101/2021.04.27.21256189},
	url = {https://www.medrxiv.org/content/early/2021/05/10/2021.04.27.21256189.1},
	author = {Thambawita, Vajira and Jonas L. {Isaksen} and Hicks, Steven and Ghouse, Jonas and Ahlberg, Gustav and Linneberg, Allan and Grarup, Niels and Ellervik, Christina and Morten Salling {Olesen} and Hansen, Torben and Graff, Claus and Holstein-Rathlou, Niels-Henrik and Str{\"u}mke, Inga and Hugo Lewi {Hammer} and Maleckar, Molly and Halvorsen, P{\r a}l and Riegler, Michael and J{\o}rgen K. {Kanters}}
}
@article {28214,
	title = {DeepFake electrocardiograms using generative adversarial networks are the beginning of the end for privacy issues in medicine},
	journal = {Nature Scientific Reports },
	volume = {11},
	year = {2021},
	month = {09/2021},
	pages = {21896},
	publisher = { Springer nature},
	abstract = {Recent global developments underscore the prominent role big data have in modern medical science. But privacy issues constitute a prevalent problem for collecting and sharing data between researchers. However, synthetic data generated to represent real data carrying similar information and distribution may alleviate the privacy issue. In this study, we present generative adversarial networks (GANs) capable of generating realistic synthetic DeepFake 10-s 12-lead electrocardiograms (ECGs). We have developed and compared two methods, named WaveGAN* and Pulse2Pulse. We trained the GANs with 7,233 real normal ECGs to produce 121,977 DeepFake normal ECGs. By verifying the ECGs using a commercial ECG interpretation program (MUSE 12SL, GE Healthcare), we demonstrate that the Pulse2Pulse GAN was superior to the WaveGAN* to produce realistic ECGs. ECG intervals and amplitudes were similar between the DeepFake and real ECGs. Although these synthetic ECGs mimic the dataset used for creation, the ECGs are not linked to any individuals and may thus be used freely. The synthetic dataset will be available as open access for researchers at OSF.io and the DeepFake generator available at the Python Package Index (PyPI) for generating synthetic ECGs. In conclusion, we were able to generate realistic synthetic ECGs using generative adversarial neural networks on normal ECGs from two population studies, thereby addressing the relevant privacy issues in medical datasets.},
	doi = {https://doi.org/10.1038/s41598-021-01295-2},
	url = {https://www.nature.com/articles/s41598-021-01295-2},
	author = {Thambawita, Vajira and Jonas L. {Isaksen} and Hicks, Steven and Ghouse, Jonas and Ahlberg, Gustav and Linneberg, Allan and Grarup, Niels and Ellervik, Christina and Morten Salling {Olesen} and Hansen, Torben and Graff, Claus and Holstein-Rathlou, Niels-Henrik and Str{\"u}mke, Inga and Hugo Lewi {Hammer} and Maleckar, Molly and Halvorsen, P{\r a}l and Riegler, Michael and J{\o}rgen K. {Kanters}}
}
@inproceedings {27834,
	title = {DeepSynthBody: the beginning of the end for data deficiency in medicine},
	journal = {The International Conference on Applied Artificial Intelligence (ICAPAI)},
	year = {2021},
	publisher = {IEEE},
	abstract = {Limited access to medical data is a barrier on developing new and efficient machine learning solutions in medicine such as computer-aided diagnosis, risk assessments, predicting optimal treatments and home-based personal healthcare systems. This paper presents DeepSynthBody: a novel framework that overcomes some of the inherent restrictions and limitations of medical data by using deep generative adversarial networks to produce synthetic data with characteristics similar to the real data, so-called DeepSynth (deep synthetic) data. We show that DeepSynthBody can address two key issues commonly associated with medical data, namely privacy concerns (as a result of data protection rules and regulations) and the high costs of annotations. To demonstrate the full pipeline of applying DeepSynthBody concepts and user-friendly functionalities, we also describe a synthetic medical dataset generated and published using our framework. DeepSynthBody opens a new era of machine learning applications in medicine with a synthetic model of the human body.},
	doi = {10.1109/ICAPAI49758.2021.9462062},
	author = {Thambawita, Vajira and Hicks, Steven and Isaksen, Jonas and Mette Haug {Stensen} and Trine B {Haugen} and Kanters, J{\o}rgen and Parasa, Sravanthi and de Lange, Thomas and H{\r a}vard D. {Johansen} and Johansen, Dag and Hugo Lewi {Hammer} and Halvorsen, P{\r a}l and Riegler, Michael}
}
@inproceedings {27833,
	title = {DivergentNets: Medical Image Segmentation by Network Ensemble},
	journal = {EndoCV},
	year = {2021},
	abstract = {Detection of colon polyps has become a trending topic in the intersecting fields of machine learning and gastrointestinal endoscopy. The focus has mainly been on per-frame classification. More recently, polyp segmentation has gained attention in the medical community. Segmentation has the advantage of being more accurate than per-frame classification or object detection as it can show the affected area in greater detail. For our contribution to the EndoCV 2021 segmentation challenge, we propose two separate approaches. First, a segmentation model named TriUNet\&nbsp;composed of three separate UNet models. Second, we combine TriUNet with an ensemble of well-known segmentation models, namely UNet++, FPN, DeepLabv3, and DeepLabv3+, into a model called DivergentNets\&nbsp;to produce more generalizable medical image segmentation masks. In addition, we propose a modified Dice loss that calculates loss only for a single class when performing multi-class segmentation, forcing the model to focus on what is most important. Overall, the proposed methods achieved the best average scores for each respective round in the challenge, with TriUNet being the winning model in Round I\&nbsp;and DvergentNets being the winning model in Round II\&nbsp;of the segmentation generalization challenge at EndoCV 2021},
	author = {Thambawita, Vajira and Hicks, Steven and Halvorsen, P{\r a}l and Riegler, Michael}
}
@inproceedings {28095,
	title = {Dutkat: A Multimedia System for Catching Illegal Catchers in a Privacy-Preserving Manner},
	journal = {Proceedings of the 2021 Workshop on Intelligent Cross-Data Analysis and Retrieval (ICDAR{\textquoteright}21)},
	year = {2021},
	pages = {57-61},
	publisher = {ACM},
	address = {New York, NY, USA},
	abstract = {Fish crime is considered a global and serious problem for a healthy and sustainable development of one of mankind{\textquoteright}s important sources of food. Technological surveillance and control solutions are emerging as remedies to combat criminal activities, but such solutions might also come with impractical and negative side-effects and challenges. In this paper, we present the concept and design of a surveillance system in lieu of current surveillance trends striking a delicate balance between privacy of legal actors while simultaneously capturing evidence-based footage, sensory data, and forensic proofs of illicit activities. Our proposed novel approach is to assist human operators in the 24/7 surveillance loop of remote professional fishing activities with a privacy-preserving Artificial Intelligence (AI) surveillance system operating in the same proximity as the activities being surveyed. The system will primarily be using video surveillance data, but also other sensor data captured on the fishing vessel. Additionally, the system correlates with other sources such as reports from other fish catches in the approximate area and time, etc. Only upon true positive flagging of specific potentially illicit activities by the locally executing AI algorithms, can forensic evidence be accessed from this physical edge, the fishing vessel. Besides a more privacy-preserving solution, our edge-based AI system also benefits from much less data that has to be transferred over unreliable, low-bandwidth satellite-based networks.},
	isbn = {9781450385299},
	doi = {10.1145/346394410.1145/3463944.3469102},
	url = {https://dl.acm.org/doi/proceedings/10.1145/3463944},
	author = {Tor-Arne Schmidt {Nordmo} and Aril B. {Ovesen} and H{\r a}vard D. {Johansen} and Riegler, Michael and Halvorsen, P{\r a}l and Johansen, Dag},
	editor = {Dao, Minh-Son and Dang-Nguyen, Duc-Tien and Riegler, Michael}
}
@article {27866,
	title = {Explaining deep neural networks for knowledge discovery in electrocardiogram analysis},
	journal = {Scientific Reports},
	volume = {11},
	year = {2021},
	month = {05/2021},
	pages = {10949},
	publisher = {Springer Nature},
	abstract = {Deep learning-based tools may annotate and interpret medical data more quickly, consistently, and accurately than medical doctors. However, as medical doctors are ultimately responsible for clinical decision-making, any deep learning-based prediction should be accompanied by an explanation that a human can understand. We present an approach called electrocardiogram gradient class activation map (ECGradCAM), which is used to generate attention maps and explain the reasoning behind deep learning-based decision-making in ECG analysis. Attention maps may be used in the clinic to aid diagnosis, discover new medical knowledge, and identify novel features and characteristics of medical tests. In this paper, we showcase how ECGradCAM attention maps can unmask how a novel deep learning model measures both amplitudes and intervals in 12-lead electrocardiograms, and we show an example of how attention maps may be used to develop novel ECG features.},
	doi = {10.1038/s41598-021-90285-5},
	url = {http://www.nature.com/articles/s41598-021-90285-5h},
	author = {Hicks, Steven and Jonas L. {Isaksen} and Thambawita, Vajira and Ghouse, Jonas and Ahlberg, Gustav and Linneberg, Allan and Grarup, Niels and Str{\"u}mke, Inga and Ellervik, Christina and Morten Salling {Olesen} and Hansen, Torben and Graff, Claus and Holstein-Rathlou, Niels-Henrik and Halvorsen, P{\r a}l and Maleckar, Molly and Riegler, Michael and J{\o}rgen K. {Kanters}}
}
@inproceedings {28020,
	title = {Exploring Deep Learning Methods for Real-Time Surgical Instrument Segmentation in Laparoscopy},
	journal = {2021 IEEE EMBS International Conference on Biomedical and Health Informatics (BHI)},
	year = {2021},
	pages = {1-4},
	publisher = {IEEE},
	abstract = {Minimally Invasive Surgery (MIS) is a surgical intervention used to examine the organs inside the abdomen and has been widely used due to its effectiveness over open surgery. Due to the hardware improvements such as high definition cameras, this procedure has significantly improved and new software methods have open potential for computer-assisted procedures. However, there exists challenges and requirement to improve detection and tracking of the position of the instruments during these surgical procedures. To this end, we evaluate and compare some popular deep learning methods that can potentially be explored for the automated segmentation of surgical instruments in laparoscopy, an important step towards tool tracking. Our experimental results demonstrate that the Dual decoder attention network (DDANet) produces a superior result compared to other recent deep learning methods. DDANet produces a dice coefficient of 0.8739 and mean intersection over union of 0.8183 for the Robust Medical Instrument Segmentation (ROBUST-MIS) Challenge 2019 dataset, at a real-time speed of 101.36 frames per second which is critical for such procedures.},
	keywords = {Real-time segmentation, minimally invasive surgery, surgical instruments,  laparoscopy, deep learning},
	author = {Jha, Debesh and Ali, Sharib and Nikhil Kumar {Tomar} and Riegler, Michael and Johansen, Dag and H{\r a}vard D {Johansen} and Halvorsen, P{\r a}l}
}
@article {28094,
	title = {File System Support for Privacy-Preserving Analysis and Forensics in Low-Bandwidth Edge Environments},
	journal = {Information},
	volume = {12},
	year = {2021},
	month = {10/2021},
	pages = {430},
	publisher = {MDPI},
	abstract = {In this paper, we present initial results from our distributed edge systems research in the domain of sustainable harvesting of common good resources in the Arctic Ocean. Specifically, we are developing a digital platform for real-time privacy-preserving sustainability management in the domain of commercial fishery surveillance operations. This is in response to potentially privacy-infringing mandates from some governments to combat overfishing and other sustainability challenges. Our approach is to deploy sensory devices and distributed artificial intelligence algorithms on mobile, offshore fishing vessels and at mainland central control centers. To facilitate this, we need a novel data plane supporting efficient, available, secure, tamper-proof, and compliant data management in this weakly connected offshore environment. We have built our first prototype of Dorvu, a novel distributed file system in this context. Our devised architecture, the design trade-offs among conflicting properties, and our initial experiences are further detailed in this paper.\&nbsp;\&nbsp;},
	doi = {10.3390/info12100430},
	url = {https://www.mdpi.com/2078-2489/12/10/430},
	author = {Aril Bernhard {Ovesen} and Tor-Arne Schmidt {Nordmo} and H{\r a}vard Dagenborg {Johansen} and Riegler, Michael and Halvorsen, P{\r a}l and Johansen, Dag}
}
@inproceedings {27641,
	title = {HTAD: A Home-Tasks Activities Dataset with Wrist-accelerometer and Audio Features},
	journal = {27th International Conference on Multimedia Modeling},
	year = {2021},
	pages = {196-205},
	publisher = { Springer},
	keywords = {Accelerometer, Activity  recognition, Audio, dataset, Sensor fusion},
	author = {Garcia-Ceja, Enrique and Thambawita, Vajira and Hicks, Steven and Jha, Debesh and Jakobsen, Petter and Hugo Lewi {Hammer} and Halvorsen, P{\r a}l and Riegler, Michael}
}
@inproceedings {28136,
	title = {HYPERAKTIV: An Activity Dataset from Patients with Attention-Deficit/Hyperactivity Disorder (ADHD)},
	journal = {Proceedings of the 12th ACM Multimedia Systems Conference (MMSys {\textquoteright}21)},
	year = {2021},
	pages = {314{\textendash}319},
	publisher = {ACM},
	abstract = {Machine learning research within healthcare frequently lacks the public data needed to be fully reproducible and comparable. Datasets are often restricted due to privacy concerns and legal requirements that come with patient-related data. Consequentially, many algorithms and models get published on the same topic without a standard benchmark to measure against. Therefore, this paper presents HYPERAKTIV, a public dataset containing health, activity, and heart rate data from patients diagnosed with attention deficit hyperactivity disorder, better known as ADHD. The dataset consists of data collected from 51 patients with ADHD and 52 clinical controls. In addition to the activity and heart rate data, we also include a series of patient attributes such as their age, sex, and information about their mental state, as well as output data from a computerized neuropsychological test. Together with the presented dataset, we also provide baseline experiments using traditional machine learning algorithms to predict ADHD based on the included activity data. We hope that this dataset can be used as a starting point for computer scientists who want to contribute to the field of mental health, and as a common benchmark for future work in ADHD analysis.},
	doi = {10.1145/3458305.3478454},
	url = {https://dl.acm.org/doi/10.1145/3458305.3478454},
	author = {Hicks, Steven and Stautland, Andrea and Ole Bernt {Fasmer} and Fr{\o}land, Wenche and Hugo Lewi {Hammer} and Halvorsen, P{\r a}l and Mjeldheim, Kristin and Ketil J. {Oedegaard} and Osnes, Berge and Vigdis Elin Gi{\ae}v {Syrstad} and Riegler, Michael and Jakobsen, Petter}
}
@inproceedings {27830,
	title = {Identification of spermatozoa by unsupervised learning from video data},
	journal = {37th Virtual Annual Meeting of the European Society of Human Reproduction and Embryology (ESHRE)},
	year = {2021},
	publisher = {Oxford University Press},
	abstract = {Identification of individual sperm is essential to assess a given sperm sample{\textquoteright}s motility behavior. Existing computer-aided systems need training data based on annotations by professionals, which is resource demanding. On the other hand, data analysed by unsupervised machine learning algorithms can improve supervised algorithms that are more stable for clinical applications. Therefore, unsupervised sperm identification can improve computer-aided sperm analysis systems predicting different aspects of sperm samples. Other possible applications are assessing kinematics and counting of spermatozoa.\&nbsp;},
	author = {Thambawita, Vajira and Trine B {Haugen} and Stensen, M.H. and Witczak, Oliwia and Hugo Lewi {Hammer} and Halvorsen, P{\r a}l and Riegler, Michael}
}
@inproceedings {27832,
	title = {Impact of Image Resolution on Convolutional Neural Networks Performance in Gastrointestinal Endoscopy},
	journal = {DDW 2021},
	year = {2021},
	abstract = {Convolutional neural networks (CNNs) are increasingly used to improve and automate processes in gastroenterology, like the detection of polyps during a colonoscopy. An important input to these methods is images and videos. Up until now, no well-defined, common understanding or standard regarding the resolution of the images and video frames has been defined, and to reduce processing time and resource requirements, images are today almost always down-sampled. However, how such down-sampling and the image resolution influence the performance in context with medical data is unknown. In this work, we investigate how the resolution relates to the performance of convolutional neural networks. This can help set standards for image or video characteristics for future CNN based models in gastrointestinal endoscopy.},
	author = {Thambawita, Vajira and Hicks, Steven and Str{\"u}mke, Inga and Riegler, Michael and Halvorsen, P{\r a}l and Parasa, Sravanthi}
}
@article {28215,
	title = {Impact of Image Resolution on Deep Learning Performance in Endoscopy Image Classification: An Experimental Study Using a Large Dataset of Endoscopic Images},
	journal = {Diagnostics},
	volume = {11},
	year = {2021},
	month = {09/2021},
	publisher = {MDPI},
	abstract = {Recent trials have evaluated the efficacy of deep convolutional neural network (CNN)-based AI systems to improve lesion detection and characterization in endoscopy. Impressive results are achieved, but many medical studies use a very small image resolution to save computing resources at the cost of losing details. Today, no conventions between resolution and performance exist, and monitoring the performance of various CNN architectures as a function of image resolution provides insights into how subtleties of different lesions on endoscopy affect performance. This can help set standards for image or video characteristics for future CNN-based models in gastrointestinal (GI) endoscopy. This study examines the performance of CNNs on the HyperKvasir dataset, consisting of 10,662 images from 23 different findings. We evaluate two CNN models for endoscopic image classification under quality distortions with image resolutions ranging from 32 {\texttimes} 32 to 512 {\texttimes} 512 pixels. The performance is evaluated using two-fold cross-validation and F1-score, maximum Matthews correlation coefficient (MCC), precision, and sensitivity as metrics. Increased performance was observed with higher image resolution for all findings in the dataset. MCC was achieved at image resolutions between 512 {\texttimes} 512 pixels for classification for the entire dataset after including all subclasses. The highest performance was observed with an MCC value of 0.9002 when the models were trained on the highest resolution and tested on the same resolution. Different resolutions and their effect on CNNs are explored. We show that image resolution has a clear influence on the performance which calls for standards in the field in the future.},
	doi = {https://doi.org/10.3390/diagnostics11122183},
	url = {https://www.mdpi.com/2075-4418/11/12/2183},
	author = {Thambawita, Vajira and Str{\"u}mke, Inga and Hicks, Steven and Halvorsen, P{\r a}l and Parasa, Sravanthi and Riegler, Michael}
}
@inproceedings {27857,
	title = {Improving generalizibilty in polyp segmentation using ensemble convolutional neural network},
	journal = {3rd International Workshop and Challenge on Computer Vision in Endoscopy (EndoCV2021)},
	volume = {2886},
	year = {2021},
	publisher = {CEUR Workshop Proceedings},
	abstract = {Medical image segmentation is a crucial task in medical image analysis. Despite near expert-label performance with the application of the deep learning method in medical image segmentation, the generalization of such models in the clinical environment remains a significant challenge. Transfer learning from a large medical dataset from the same domain is a common technique to address generalizability. However, it is difficult to find a similar large medical dataset. To address generalizability in polyp segmentation, we have used an ensemble of four MultiResUNet architectures, each trained on the combination of the different centered datasets provided by the challenge organizers. Our method achieved a decent performance of 0.6172 {\textpm} 0.0778 for the multi-centered dataset. Our study shows that significant work needs to be done to develop a computer-aided diagnosis system to detect and localize polyp of the multi-center datasets, which is essential for improving the quality of the colonoscopy.},
	keywords = {colonoscopy, Convolutional neural network, health informatics, Polyp segmentation},
	author = {KumarTomar, Nikhil and Ibtehaz, Nabil and Jha, Debesh and Halvorsen, P{\r a}l and Ali, Sharib}
}
@article {27867,
	title = {Kvasir-Capsule, a video capsule endoscopy dataset},
	journal = {Scientific Data},
	volume = {8},
	year = {2021},
	pages = {142},
	publisher = {Springer Nature},
	abstract = {Artificial intelligence (AI) is predicted to have profound effects on the future of video capsule endoscopy (VCE) technology. The potential lies in improving anomaly detection while reducing manual labour. Existing work demonstrates the promising benefits of AI-based computer-assisted diagnosis systems for VCE. They also show great potential for improvements to achieve even better results. Also, medical data is often sparse and unavailable to the research community, and qualified medical personnel rarely have time for the tedious labelling work. We present\&nbsp;Kvasir-Capsule, a large VCE dataset collected from examinations at a Norwegian Hospital.\&nbsp;Kvasir-Capsule\&nbsp;consists of 117 videos which can be used to extract a total of 4,741,504 image frames. We have labelled and medically verified 47,238 frames with a bounding box around findings from 14 different classes. In addition to these labelled images, there are 4,694,266 unlabelled frames included in the dataset. The\&nbsp;Kvasir-Capsule\&nbsp;dataset can play a valuable role in developing better algorithms in order to reach true potential of VCE technology.},
	doi = {10.1038/s41597-021-00920-z},
	url = {http://www.nature.com/articles/s41597-021-00920-z},
	author = {Pia H. {Smedsrud} and Thambawita, Vajira and Hicks, Steven and Gjestang, Henrik and Oda Olsen {Nedrejord} and N{\ae}ss, Espen and Borgli, Hanna and Jha, Debesh and Tor Jan Derek {Berstad} and Sigrun L. {Eskeland} and Lux, Mathias and Espeland, H{\r a}vard and Petlund, Andreas and Duc Tien Dang {Nguyen} and Garcia-Ceja, Enrique and Johansen, Dag and Peter T. {Schmidt} and Toth, Ervin and Hugo Lewi {Hammer} and de Lange, Thomas and Riegler, Michael and Halvorsen, P{\r a}l}
}
@inproceedings {27511,
	title = {Kvasir-Instrument: Diagnostic and therapeutic tool segmentation dataset in gastrointestinal endoscopy},
	journal = {27th International Conference on Multimedia Modeling},
	volume = {LNCS, volume 12573},
	year = {2021},
	pages = {218-229},
	publisher = {Springer},
	abstract = {Gastrointestinal (GI) pathologies are periodically screened, biopsied, and resected using surgical tools. Usually the procedures and the treated or resected areas are not specifically tracked or analysed during or after colonoscopies. Information regarding disease borders, development and amount and size of the resected area get lost. This can lead to poor follow-up and bothersome reassessment difficulties post-treatment. To improve the current standard and also to foster more research on the topic we have released the\&nbsp; {\textquoteleft}{\textquoteleft}Kvasir Instrument{\textquoteright}{\textquoteright} dataset which consists of $590$ annotated frames containing GI procedure tools such as snares, balloons and biopsy forceps, etc. Beside of the images, the dataset includes ground truth masks and bounding boxes and has been verified by two expert GI endoscopists. Additionally, we provide a baseline for the segmentation of the GI tools to promote research and algorithm development. We obtained a dice coefficient score of 0.9158 and a Jaccard index of 0.8578 using a classical U-Net architecture. A similar dice coefficient score was observed for DoubleUNet. The qualitative results showed that the model did not work for the images with specularity and the frames with multiple instruments, while the best result for both methods was observed on all other types of images. Both, qualitative and quantitative results show that the model performs reasonably good, but there is a large potential for further improvements.\&nbsp; Benchmarking using the dataset provides an opportunity for researchers to contribute to the field of automatic endoscopic diagnostic and therapeutic tool segmentation for GI endoscopy.\&nbsp;},
	author = {Jha, Debesh and Ali, Sharib and Emanuelsen, Krister and Hicks, Steven and Thambawita, Vajira and Garcia-Ceja, Enrique and Riegler, Michael and de Lange, Thomas and Peter T. {Schmidt} and H{\r a}vard D. {Johansen} and Johansen, Dag and Halvorsen, P{\r a}l}
}
@article {28228,
	title = {MedAI: Transparency in Medical Image Segmentation},
	journal = {Nordic Machine Intelligence},
	volume = {1},
	year = {2021},
	month = {Jan-11-2021},
	pages = {1 - 4},
	publisher = {NMI},
	address = {Oslo},
	doi = {10.5617/nmi.9140},
	url = {https://journals.uio.no/NMI/article/view/9140https://journals.uio.no/NMI/article/download/9140/7753https://journals.uio.no/NMI/article/download/9140/7753},
	author = {Hicks, Steven and Jha, Debesh and Thambawita, Vajira and Halvorsen, P{\r a}l and Singstad, Bj{\o}rn-Jostein and Gaur, Sachin and Pettersen, Klas and Goodwin, Morten and Parasa, Sravanthi and de Lange, Thomas and Riegler, Michael}
}
@inproceedings {40625,
	title = {Medico Multimedia Task at MediaEval 2021: Transparency in Medical Image Segmentation},
	journal = {Mediaeval Medico 2021},
	year = {2021},
	publisher = {Mediaeval 2021},
	abstract = {The Medico Multimedia Task\&nbsp;focuses on providing multimedia researchers with the opportunity to contribute to different areas of medicine using multimedia data to solve several subtasks. This year, the task focuses on transparency within machine learning-based medical segmentation systems, where the use case is gastrointestinal endoscopy. In this paper, we motivate the organization of this task, describe the development and test dataset, and present the evaluation process used to assess the participants{\textquoteright} submissions.},
	url = {https://2021.multimediaeval.com/},
	author = {Hicks, Steven and Jha, Debesh and Thambawita, Vajira and Hugo Lewi {Hammer} and de Lange, Thomas and Parasa, Sravanthi and Riegler, Michael and Halvorsen, P{\r a}l}
}
@misc {aneja2021mmsys21,
	title = {MMSys{\textquoteright}21 Grand Challenge on Detecting Cheapfakes},
	year = {2021},
	publisher = {arXiv},
	author = {Aneja, Shivangi and Midoglu, Cise and Dang-Nguyen, Duc-Tien and Riegler, Michael and Halvorsen, P{\r a}l and Niessner, Matthias and Adsumilli, Balu and Bregler, Chris}
}
@inproceedings {28008,
	title = {Multimodal Virtual Avatars for Investigative Interviews with Children},
	journal = {Proceedings of the 2021 Workshop on Intelligent Cross-Data Analysis and Retrieval (ICDAR {\textquoteright}21)},
	year = {2021},
	publisher = {ACM},
	address = {New York, NY, USA},
	abstract = {In this article, we present our ongoing work in the field of training police officers who conduct interviews with abused children. The objectives in this context are to protect vulnerable children from abuse, facilitate prosecution of offenders, and ensure that innocent adults are not accused of criminal acts. There is therefore a need for more data that can be used for improved interviewer training to equip police with the skills to conduct high-quality interviews. To support this important task, we propose to research a training program that utilizes different system components and multimodal data from the field of artificial intelligence such as chatbots, generation of visual content, text-to-speech, and speech-to-text. This program will be able to generate an almost unlimited amount of interview and also training data. The goal of combining all these different technologies and datatypes is to create an immersive and interactive child avatar that responds in a realistic way, to help to support the training of police interviewers, but can also produce synthetic data of interview situations that can be used to solve different problems in the same domain.},
	isbn = {9781450385299},
	doi = {10.1145/346394410.1145/3463944.3469269},
	url = {https://dl.acm.org/doi/proceedings/10.1145/3463944},
	author = {Gunn Astrid {Baugerud} and Miriam S. {Johnson} and Ragnhild Klingenber {R{\o}ed} and Michael E. {Lamb} and Powell, Martine and Thambawita, Vajira and Hicks, Steven and Salehi, Pegah and Syed Zohaib {Hassan} and Halvorsen, P{\r a}l and Riegler, Michael},
	editor = {Dao, Minh-Son and Dang-Nguyen, Duc-Tien and Riegler, Michael}
}
@inproceedings {27856,
	title = {NanoNet: Real-Time Polyp Segmentation in Video Capsule Endoscopy and Colonoscopy},
	journal = {34th IEEE CBMS International Symposium on Computer-Based Medical Systems},
	year = {2021},
	publisher = { IEEE},
	abstract = {Deep learning in gastrointestinal endoscopy can assist to improve clinical performance and be helpful to assess lesions more accurately. To this extent, semantic segmentation methods that can perform automated real-time delineation of a region-of-interest, e.g., boundary identification of cancer or precancerous lesions, can benefit both diagnosis and interventions. However, accurate and real-time segmentation of endoscopic images is extremely challenging due to its high operator dependence and high-definition image quality. To utilize automated methods in clinical settings, it is crucial to design lightweight models with low latency such that they can be integrated with low-end endoscope hardware devices. In this work, we propose NanoNet, a novel architecture for the segmentation of video capsule endoscopy and colonoscopy images. Our proposed architecture allows real-time performance and has higher segmentation accuracy compared to other more complex ones. We use video capsule endoscopy and standard colonoscopy datasets with polyps, and a dataset consisting of endoscopy biopsies and surgical instruments, to evaluate the effectiveness of our approach. Our experiments demonstrate the increased performance of our architecture in terms of a trade-off between model complexity, speed, model parameters, and metric performances. Moreover, the resulting model size is relatively tiny, with only nearly 36,000 parameters compared to traditional deep learning approaches having millions of parameters.},
	keywords = {colonoscopy, deep learning, segmentation, tool  segmentation, Video capsule endoscopy},
	author = {Jha, Debesh and Nikhil Kumar {Tomar} and Ali, Sharib and Riegler, Michael and H{\r a}vard D {Johansen} and Johansen, Dag and de Lange, Thomas and Halvorsen, P{\r a}l}
}
@inproceedings {28229,
	title = {Njord: An out-in-the-wild real world fish vessel catch analysis dataset},
	journal = {Arctic Frontiers},
	year = {2021},
	publisher = {Arctic Frontiers},
	address = {Troms{\o}, Norway},
	author = {Riegler, Michael and Johansen, Dag and Bj{\o}rn Aslak {Juliussen} and Tor-Arne Schmidt {Nordmo} and Aril Bernhard {Ovesen} and Halvorsen, P{\r a}l and H{\r a}vard D. {Johansen} and Jon Petter {Rui}}
}
@inproceedings {39299,
	title = {PAANet: Progressive Alternating Attention for Automatic Medical Image Segmentation},
	journal = {Proc. of 2021 4th International Conference on Bio-Engineering for Smart Technologies (BioSMART)},
	year = {2021},
	month = {12/2021},
	publisher = {IEEE},
	address = {Paris / Cr{\'e}teil, France},
	abstract = {Medical image segmentation can provide detailed information for clinical analysis which can be useful for scenarios where the detailed location of a finding is important. Knowing the location of a disease can play a vital role in treatment and decision-making. Convolutional neural network (CNN) based encoder-decoder techniques have advanced the performance of automated medical image segmentation systems. Several such CNN-based methodologies utilize techniques such as spatial- and channel-wise attention to enhance performance. Another technique that has drawn attention in recent years is residual dense blocks (RDBs). The successive convolutional layers in densely connected blocks are capable of extracting diverse features with varied receptive fields and thus, enhancing performance. However, consecutive stacked convolutional operators may not necessarily generate features that facilitate the identification of the target structures. In this paper, we propose a progressive alternating attention network (PAANet). We develop progressive alternating attention dense (PAAD) blocks, which construct a guiding attention map (GAM) after every convolutional layer in the dense blocks using features from all scales. The GAM allows the following layers in the dense blocks to focus on the spatial locations relevant to the target region. Every alternatePAAD block inverts the GAM to generate a reverse attention map which guides ensuing layers to extract boundary and edge-related information, refining the segmentation process. Our experiments on three different biomedical image segmentation datasets exhibit that our PAANet achieves favorable performance when compared to other state-of-the-art methods.\&nbsp;},
	doi = {10.1109/BioSMART54244.2021.9677844},
	url = {https://ieeexplore.ieee.org/document/9677844},
	author = {Srivastava, Abhishek and Chanda, Sukalpa and Jha, Debesh and Riegler, Michael and Halvorsen, P{\r a}l and Johansen, Dag and Pal, Umapada}
}
@article {27773,
	title = {Real-Time Polyp Detection, Localization and Segmentation in Colonoscopy Using Deep Learning},
	journal = {IEEE Access},
	volume = {9},
	year = {2021},
	pages = {40496-40510},
	publisher = { IEEE},
	abstract = {Computer-aided detection, localization, and segmentation methods can help improve colonoscopy procedures. Even though many methods have been built to tackle automatic detection and segmentation of polyps, benchmarking of state-of-the-art methods still remains an open problem. This is due to the increasing number of researched computer vision methods that can be applied to polyp datasets. Benchmarking of novel methods can provide a direction to the development of automated polyp detection and segmentation tasks. Furthermore, it ensures that the produced results in the community are reproducible and provide a fair comparison of developed methods. In this paper, we benchmark several recent state-of-the-art methods using Kvasir-SEG, an open-access dataset of colonoscopy images for polyp detection, localization, and segmentation evaluating both method accuracy and speed. Whilst, most methods in literature have competitive performance over accuracy, we show that the proposed ColonSegNet achieved a better trade-off between an average precision of 0.8000 and mean IoU of 0.8100, and the fastest speed of 180 frames per second for the detection and localization task. Likewise, the proposed ColonSegNetachieved a competitive dice coefficient of 0.8206 and the best average speed of 182.38 frames per second for the segmentation task. Our comprehensive comparison with various state-of-the-art methods reveals the importance of benchmarking the deep learning methods for automated real-time polyp identification and delineations that can potentially transform current clinical practices and minimize miss-detection rates.},
	keywords = {Medical image segmentation,  ColonSegNet, colonoscopy, polyps, deep learning, detection, localization, benchmarking, Kvasir-SEG},
	doi = {10.1109/ACCESS.2021.3063716},
	author = {Jha, Debesh and Ali, Sharib and Nikhil Kumar {Tomar} and H{\r a}vard D {Johansen} and Johansen, Dag and Rittscher, Jens and Riegler, Michael and Halvorsen, P{\r a}l}
}
@article {27908,
	title = {SmartIO: Zero-overhead Device Sharing through PCIe Networking},
	journal = {ACM Transactions on Computer Systems},
	volume = {38},
	number = {2},
	year = {2021},
	month = {07/2021},
	pages = { 1{\textendash}78},
	publisher = {Association for Computing Machinery},
	address = {New York, NY, United States},
	abstract = {The large variety of compute-heavy and data-driven applications accelerate the need for a distributed I/O solution that enables cost-effective scaling of resources between networked hosts. For example, in a cluster system, different machines may have various devices available at different times, but moving workloads to remote units over the network is often costly and introduces large overheads compared to accessing local resources. To facilitate I/O disaggregation and device sharing among hosts connected using Peripheral Component Interconnect Express (PCIe) non-transparent bridges, we present SmartIO. NVMes, GPUs, network adapters, or any other standard PCIe device may be borrowed and accessed directly, as if they were local to the remote machines. We provide capabilities beyond existing disaggregation solutions by combining traditional I/O with distributed shared-memory functionality, allowing devices to become part of the same global address space as cluster applications. Software is entirely removed from the data path, and simultaneous sharing of a device among application processes running on remote hosts is enabled. Our experimental results show that I/O devices can be shared with remote hosts, achieving native PCIe performance. Thus, compared to existing device distribution mechanisms, SmartIO provides more efficient, low-cost resource sharing, increasing the overall system performance},
	issn = {0734-2071},
	doi = {https://doi.org/10.1145/3462545},
	url = {https://dl.acm.org/doi/10.1145/3462545},
	author = {Markussen, Jonas and Lars Bj{\o}rlykke {Kristiansen} and Halvorsen, P{\r a}l and Kielland-Gyrud, Halvor and H{\r a}kon Kvale {Stensland} and Griwodz, Carsten}
}
@inproceedings {28230,
	title = {Sustainable Commercial Fishing: Digital Inspectors to the Rescue},
	journal = {Arctic Frontiers},
	year = {2021},
	publisher = {Arctic Frontiers},
	author = {Johansen, Dag and Bj{\o}rn Aslak {Juliussen} and Tor-Arne Schmidt {Nordmo} and Aril Bernhard {Ovesen} and Halvorsen, P{\r a}l and H{\r a}vard Dagenborg {Johansen} and Riegler, Michael and Jon Petter {Rui}}
}
@inproceedings {42518,
	title = {Transfer Learning in Polyp and Endoscopic Tool Segmentation from Colonoscopy Images},
	journal = {Nordic Machine Intelligence},
	volume = {1},
	year = {2021},
	month = {11/2021},
	pages = {32 - 34},
	publisher = {Nordic Machine Intelligence},
	edition = {1},
	abstract = {Colorectal cancer is one of the deadliest and most widespread types of cancer in the world. Colonoscopy is the procedure used to detect and diagnose polyps from the colon, but today{\textquoteright}s detection rate shows a significant error rate that affects diagnosis and treatment. An automatic image segmentation algorithm may help doctors to improve the detection rate of pathological polyps in the colon. Furthermore, segmenting endoscopic tools in images taken during colonoscopy may contribute towards robotic assisted surgery. In this study, we trained and validated both pre-trained and not pre-trained segmentation models on two different data sets, containing images of polyps and endoscopic tools. Finally, we applied the models on two separate test sets and the best polyp model got a dice score 0.857 and the test instrument model got a dice score 0.948. Moreover, we found that pre-training of the models increased the performance in segmenting polyps and endoscopic tools.},
	keywords = {convolutional neural networks, Hyperkvasir, MedAI challenge, Polyp segmentation, Transfer Learning},
	issn = {2703-9196},
	doi = {10.5617/nmi.9132},
	url = {https://journals.uio.no/NMI/article/view/9132},
	author = {Nefeli PanagiotaN {TzavaraTzavara} and Singstad, Bj{\o}rn-Jostein},
	editor = {Riegler, Michael and Hicks, Steven and Halvorsen, P{\r a}l and Thambawita, Vajira}
}
@article {28007,
	title = {Using 3D Convolutional Neural Networks for Real-time Detection of Soccer Events},
	journal = {International Journal of Semantic Computing},
	volume = {15},
	number = {2},
	year = {2021},
	month = {Jan-06-2021},
	pages = {161 - 187},
	publisher = {World Scientific},
	abstract = {Developing systems for the automatic detection of events in video is a task which has gained attention in many areas including sports. More specifically, event detection for soccer videos has been studied widely in the literature. However, there are still a number of shortcomings in the state-of-the-art such as high latency, making it challenging to operate at the live edge. In this paper, we present an algorithm to detect events in soccer videos in real time, using 3D convolutional neural networks. We test our algorithm on three different datasets from SoccerNet, the Swedish Allsvenskan, and the Norwegian Eliteserien. Overall, the results show that we can detect events with high recall, low latency, and accurate time estimation. The trade-off is a slightly lower precision compared to the current state-of-the-art, which has higher latency and performs better when a less accurate time estimation can be accepted. In addition to the presented algorithm, we perform an extensive ablation study on how the different parts of the training pipeline affect the final results.},
	keywords = {3d CNN, classification, Detection, soccer events, spotting},
	issn = {1793-351X},
	doi = {10.1142/S1793351X2140002X},
	url = {https://www.worldscientific.com/doi/abs/10.1142/S1793351X2140002X},
	author = {Olav A. Nerg{\r a}r {Rongved} and Hicks, Steven and Thambawita, Vajira and H{\r a}kon Kvale {Stensland} and Zouganeli, Evi and Johansen, Dag and Midoglu, Cise and Riegler, Michael and Halvorsen, P{\r a}l}
}
@inproceedings {42767,
	title = {Visual Sentiment Analysis: A Natural Disaster Use-case Task at MediaEval 2021},
	journal = {MediaEval 2021},
	year = {2021},
	publisher = {Ceurws},
	author = {Syed Zohaib {Hassan} and Ahmad, Kashif and Riegler, Michael and Hicks, Steven and Conci, Nicola and Halvorsen, P{\r a}l and Al-Fuqaha, Ala}
}
@inproceedings {10.1145/3394171.3416287,
	title = {ACM Multimedia BioMedia 2020 Grand Challenge Overview},
	journal = {Proceedings of the 28th ACM International Conference on Multimedia},
	year = {2020},
	pages = {4655{\textendash}4658},
	publisher = {Association for Computing Machinery},
	address = {New York, NY, USA},
	abstract = {The BioMedia 2020 ACM Multimedia Grand Challenge is the second in a series of competitions focusing on the use of multimedia for different medical use-cases. In this year{\textquoteright}s challenge, participants are asked to develop algorithms that automatically predict the quality of a given human semen sample using a combination of visual, patient-related, and laboratory-analysis-related data. Compared to last year{\textquoteright}s challenge, participants are provided with a fully multimodal dataset (videos, analysis data, study participant data) from the field of assisted human reproduction. The tasks encourage the use of the different modalities contained within the dataset and finding smart ways of how they may be combined to further improve prediction accuracy. For example, using only video data or combining video data and patient-related data. The ground truth was developed through a preliminary analysis done by medical experts following the World Health Organization{\textquoteright}s standard for semen quality assessment. The task lays the basis for automatic, real-time support systems for artificial reproduction. We hope that this challenge motivates multimedia researchers to explore more medical-related applications and use their vast knowledge to make a real impact on people{\textquoteright}s lives.},
	keywords = {artificial intelligence, Machine learning, male fertility, semen analysis, spermatozoa},
	isbn = {9781450379885},
	doi = {10.1145/3394171.3416287},
	url = {https://doi.org/10.1145/3394171.3416287},
	author = {Hicks, Steven and Thambawita, Vajira and Hugo Lewi {Hammer} and Trine B. {Haugen} and Jorunn M. {Andersen} and Witczak, Oliwia and Halvorsen, P{\r a}l and Riegler, Michael}
}
@article {27638,
	title = {Comparative validation of multi-instance instrument segmentation in endoscopy: results of the ROBUST-MIS 2019 challenge},
	journal = {Medical Image Analysis},
	year = {2020},
	month = {11/2020},
	publisher = {Elsevier},
	abstract = {Intraoperative tracking of laparoscopic instruments is often a prerequisite for computer and robotic-assisted interventions. While numerous methods for detecting,\&nbsp; segmenting and tracking of medical instruments based on endoscopic video im-ages have been proposed in the literature, key limitations remain to be addressed:\&nbsp; Firstly, robustness, that is, the reliable performance of state-of-the-art methods when run on challenging images (e.g. in the presence of blood, smoke or motion artifacts).\&nbsp; Secondly, generalization; algorithms trained for a specific intervention in a specific hospital should generalize to other interventions or institutions. In\&nbsp;an\&nbsp;effort\&nbsp;to\&nbsp;promote\&nbsp;solutions\&nbsp;for\&nbsp;these\&nbsp;limitations,\&nbsp; we\&nbsp;organized\&nbsp;the Robust\&nbsp; Medical\&nbsp; Instrument\&nbsp; Segmentation (ROBUST-MIS) challenge as an international benchmarking competition with a specific focus on the robustness and generalization capabilities of algorithms.\&nbsp; For the first time in the field of endoscopic image processing, our challenge included a task on binary segmentation and also addressed multi-instance detection and segmentation.\&nbsp; The challenge was based on a surgical data set comprising 10,040 annotated images acquired from a total of 30 surgical procedures from three different types of surgery. The validation of the competing methods for the three tasks (binary segmentation, multi-instance detection and multi-instance segmentation) was performed in three different stages with an increasing domain gap between the training and the test data. The results confirm the initial hypothesis, namely that algorithm performance degrades with an increasing domain gap. While the average detection and segmentation quality of the best-performing algorithms is high, future research should concentrate on detection and segmentation of small, crossing, moving and transparent instrument(s) (parts).\&nbsp;},
	author = {Ro{\ss}, Tobias and Reinke, Annika and Peter M. {Full} and Wagner, Martin and Kenngott, Hannes and Apitz, Martin and Hempe, Hellena and Diana Mindroc {Filimon} and Scholz, Patrick and Thuy Nuong {Tran} and Bruno, Pierangela and Pablo Arbel ́ {aez} and Bin Bian, Gui- and Bodenstedt, Sebastian and Jon Lindstrom {Bolmgren} and Laura Bravo-S ́ {anchez} and Bin Chen, Hua- and Cristina Gonz ́ {alez} and Guo, Dong and Halvorsen, P{\r a}l and Heng, Pheng-Ann and Hosgor, Enes and Hou, Zeng-Guang and Isensee, Fabian and Jha, Debesh and Jiang, Tingting and Jin, Yueming and Kirtac, Kadir and Kletz, Sabrina and Leger, Stefan and Li, Zhixuan and Klaus H. {Maier-Hein} and Ni, Zhen-Liang and Riegler, Michael and Schoeffmann, Klaus and Shi, Ruohua and Speidel, Stefanie and Stenzel, Michael and Twick, Isabell and Wang, Gutai and Wang, iacheng and Wang, Liansheng and Wang, Lu and Zhang, Yujie and Zhou, Yan-Jie and Zhu, Lei and Wiesenfarth, Manuel and Kopp-Schneider, Annette and Beat P. M ̈ {uller-Stich} and Maier-Hein, Lena}
}
@inproceedings {27324,
	title = {DoubleU-Net: A Deep Convolutional Neural Network for Medical Image Segmentation},
	journal = {CBMS 2020: International Symposium on Computer-Based Medical Systems},
	year = {2020},
	note = {This paper was nominated for the best paper award at CBMS 2020.\&nbsp;},
	publisher = { IEEE},
	author = {Jha, Debesh and Riegler, Michael and Johansen, Dag and Halvorsen, P{\r a}l and H{\r a}vard D {Johansen}}
}
@inproceedings {27558,
	title = {The EndoTect 2020 Challenge: Evaluation and Comparison of Classification, Segmentation and Inference Time for Endoscopy},
	journal = {25th International Conference on Pattern Recognition (ICPR)},
	year = {2020},
	publisher = {IEEE},
	abstract = {The EndoTect challenge at the International Conference on Pattern Recognition 2020 aims to motivate the development of algorithms that aid medical experts in finding anomalies that commonly occur in the gastrointestinal tract. Using HyperKvasir, a large dataset containing images taken from several endoscopies, the participants competed in three tasks. Each task focuses on a specific requirement for making it useful in a real-world medical scenario. The tasks are (i) high classification performance in terms of prediction accuracy, (ii) efficient classification measured by the number of images classified per second, and (iii) pixel-level segmentation of specific anomalies. Hopefully, this can motivate different computer science researchers to help benchmark a crucial component of a future computer-aided diagnosis system, which in turn, could potentially save human lives.},
	author = {Hicks, Steven and Jha, Debesh and Thambawita, Vajira and Halvorsen, P{\r a}l and Hugo Lewi {Hammer} and Riegler, Michael}
}
@article {27265,
	title = {An Extensive Study on Cross-Dataset Bias and Evaluation Metrics Interpretation for Machine Learning applied to Gastrointestinal Tract Abnormality Classification},
	journal = {ACM Transactions on Computing for Healthcare},
	volume = {1},
	number = {3},
	year = {2020},
	pages = {1-29},
	publisher = {ACM},
	abstract = {Precise and efficient automated identification of Gastrointestinal (GI) tract diseases can help doctors treat more patients and improve the rate of disease detection and identification. Currently, automatic analysis of diseases in the GI tract is a hot topic in both computer science and medical-related journals. Nevertheless, the evaluation of such an automatic analysis is often incomplete or simply wrong. Algorithms are often only tested on small and biased datasets, and cross-dataset evaluations are rarely performed. A clear understanding of evaluation metrics and machine learning models with cross datasets is crucial to bring research in the field to a new quality level. Towards this goal, we present comprehensive evaluations of five distinct machine learning models using Global Features and Deep Neural Networks that can classify 16 different key types of GI tract conditions, including pathological findings, anatomical landmarks, polyp removal conditions, and normal findings from images captured by common GI tract examination instruments. Inour evaluation, we introduce performance hexagons using six performance metrics such as recall, precision, specificity, accuracy, F1-score, and Matthews Correlation Coefficient to demonstrate how to determine the real capabilities of models rather than evaluatingthem shallowly. Furthermore, we perform cross-dataset evaluations using different datasets for training and testing. With these cross-dataset evaluations, we demonstrate the challenge of actually building a generalizable model that could be used across different hospitals. Our experiments clearly show that more sophisticated performance metrics and evaluation methods need to be applied to get reliable models rather than depending on evaluations of the splits of the same dataset, i.e., the performance metrics should always be interpreted together rather than relying on a single metric.},
	author = {Thambawita, Vajira and Jha, Debesh and Hugo Lewi {Hammer} and H{\r a}vard D {Johansen} and Johansen, Dag and Halvorsen, P{\r a}l and Riegler, Michael}
}
@article {27472,
	title = {HyperKvasir, a comprehensive multi-class image and video dataset for gastrointestinal endoscopy},
	journal = {Scientific Data},
	volume = {7},
	year = {2020},
	month = {08/2020},
	pages = {1-14},
	publisher = {Springer Nature},
	abstract = {Artificial intelligence is currently a hot topic in medicine. However, medical data is often sparse and hard to obtain due to legal restrictions and lack of medical personnel for the cumbersome and tedious process to manually label training data. These constraints make it difficult to develop systems for automatic analysis, like detecting disease or other lesions. In this respect, this article presents\&nbsp;HyperKvasir, the largest image and video dataset of the gastrointestinal tract available today. The data is collected during real gastro- and colonoscopy examinations at B{\ae}rum Hospital in Norway and partly labeled by experienced gastrointestinal endoscopists. The dataset contains 110,079 images and 374 videos, and represents anatomical landmarks as well as pathological and normal findings. The total number of images and video frames together is around 1 million. Initial experiments demonstrate the potential benefits of artificial intelligence-based computer-assisted diagnosis systems. The\&nbsp;HyperKvasir\&nbsp;dataset can play a valuable role in developing better algorithms and computer-assisted examination systems not only for gastro- and colonoscopy, but also for other fields in medicine.},
	keywords = {dataset, GI, Machine learning},
	doi = {10.1038/s41597-020-00622-y},
	url = {http://www.nature.com/articles/s41597-020-00622-y},
	author = {Borgli, Hanna and Thambawita, Vajira and Pia H. {Smedsrud} and Hicks, Steven and Jha, Debesh and Sigrun L. {Eskeland} and Kristin Ranheim {Randel} and Pogorelov, Konstantin and Lux, Mathias and Duc Tien Dang {Nguyen} and Johansen, Dag and Griwodz, Carsten and H{\r a}kon Kvale {Stensland} and Garcia-Ceja, Enrique and Peter T. {Schmidt} and Hugo Lewi {Hammer} and Riegler, Michael and Halvorsen, P{\r a}l and de Lange, Thomas}
}
@inproceedings {27473,
	title = {ImageCLEF 2020: Multimedia Retrieval in Lifelogging, Medical, Nature, and Internet Applications},
	journal = {European Conference on Information Retrieval},
	year = {2020},
	pages = {533 - 541},
	publisher = {Springer International Publishing},
	address = {Cham},
	abstract = {This paper presents an overview of the 2020 ImageCLEF lab that will be organized as part of the Conference and Labs of the Evaluation Forum{\textemdash}CLEF Labs 2020 in Thessaloniki, Greece. ImageCLEF is an ongoing evaluation initiative (run since 2003) that promotes the evaluation of technologies for annotation, indexing and retrieval of visual data with the aim of providing information access to large collections of images in various usage scenarios and domains. In 2020, the 18th edition of ImageCLEF will organize four main tasks: (i) a\&nbsp;Lifelog\&nbsp;task (videos, images and other sources) about daily activity understanding, retrieval and summarization, (ii) a\&nbsp;Medical\&nbsp;task that groups three previous tasks (caption analysis, tuberculosis prediction, and medical visual question answering) with new data and adapted tasks, (iii) a\&nbsp;Coral\&nbsp;task about segmenting and labeling collections of coral images for 3D modeling, and a new (iv)\&nbsp;Web user interface\&nbsp;task addressing the problems of detecting and recognizing hand drawn website UIs (User Interfaces) for generating automatic code. The strong participation, with over 235 research groups registering and 63 submitting over 359 runs for the tasks in 2019 shows an important interest in this benchmarking campaign. We expect the new tasks to attract at least as many researchers for 2020.},
	isbn = {978-3-030-45441-8},
	issn = {0302-9743},
	doi = {10.1007/978-3-030-45442-5_69},
	url = {https://link.springer.com/chapter/10.1007/978-3-030-45442-5_69},
	author = {Ionescu, Bogdan and M{\"u}ller, Henning and P{\'e}teri, Renaud and Dang-Nguyen, Duc-Tien and Zhou, Liting and Piras, Luca and Riegler, Michael and Halvorsen, P{\r a}l and Tran, Minh-Triet and Lux, Mathias and Gurrin, Cathal and Chamberlain, Jon and Clark, Adrian and Campello, Antonio and Alba G. Seco {de Herrera} and Ben Abacha, Asma and Datla, Vivek and Sadid A. {Hasan} and Liu, Joey and Demner-Fushman, Dina and Pelka, Obioma and Christoph M. {Friedrich} and Yashin Dicente {Cid} and Kozlovski, Serge and Liauchuk, Vitali and Kovalev, Vassili and Berari, Raul and Brie, Paul and Fichou, Dimitri and Dogariu, Mihai and Liviu Daniel {Stefan} and Mihai Gabriel {Constantin}},
	editor = {Joemon M. {Jose} and Yilmaz, Emine and Magalh{\~a}es, Jo{\~a}o and Castells, Pablo and Ferro, Nicola and M{\'a}rio J. {Silva} and Martins, Fl{\'a}vio}
}
@inproceedings {39534,
	title = {Kvasir-instrument: Diagnostic and therapeutic tool segmentation dataset in gastrointestinal endoscopy},
	journal = {International Conference on Multimedia Modeling},
	year = {2020},
	publisher = { Springer},
	abstract = {Gastrointestinal\&nbsp;pathologies are periodically screened, biopsied, and resected using surgical tools. Usually, the procedures and the treated or resected areas are not specifically tracked or analysed during or after colonoscopies. Information regarding disease borders, development,\&nbsp; amount, and size of the resected area get lost. This can lead to poor follow-up and bothersome reassessment difficulties post-treatment. To improve the current standard and also to foster more research on the topic, we have released the\&nbsp; {\textquoteleft}{\textquoteleft}Kvasir-Instrument{\textquoteright}{\textquoteright} dataset, which consists of 590\&nbsp;annotated frames containing GI\&nbsp;procedure tools such as snares, balloons, and biopsy forceps, etc. Besides the images, the dataset includes ground truth masks and bounding boxes and has been verified by two expert GI\&nbsp;endoscopists. Additionally, we provide a baseline for the segmentation of the GI tools to promote research and algorithm development. We obtained a dice coefficient score of 0.9158\&nbsp;and a Jaccard index of 0.8578\&nbsp;using a classical U-Net architecture. A similar dice coefficient score was observed for DoubleUNet. The qualitative results showed that the model did not work for the images with specularity and the frames with multiple tools, while the best result for both methods was observed on all other types of images. Both qualitative and quantitative results show that the model performs reasonably good, but there is potential for further improvements.\&nbsp; Benchmarking using the dataset provides an opportunity for researchers to contribute to the field of automatic endoscopic diagnostic and therapeutic tool segmentation for GI\&nbsp;endoscopy.},
	keywords = {Benchmarking, Convolutional  neural network, Gastrointestinal endoscopy, Tool segmentation},
	url = {https://www.springerprofessional.de/en/kvasir-instrument-diagnostic-and-therapeutic-tool-segmentation-d/18788368},
	author = {Jha, Debesh and Ali, Sharib and Emanuelsen, Krister and Hicks, Steven and Thambawita, Vajira and Garcia-Ceja, Enrique and Riegler, Michael and de Lange, Thomas and Peter T. {Schmidt} and H{\r a}vard D {Johansen} and Johansen, Dag and Halvorsen, P{\r a}l}
}
@inproceedings {26811,
	title = {Kvasir-SEG: A Segmented Polyp Dataset},
	journal = {International Conference on Multimedia Modeling},
	year = {2020},
	pages = {451-462},
	publisher = {Springer},
	address = {Daejeon, Korea},
	abstract = {Pixel-wise image segmentation is a highly demanding task in medical image analysis. In practice, it is difficult to find annotated medical images with corresponding segmentation masks. In this paper, we present\&nbsp; Kvasir-SEG: an open-access dataset of gastrointestinal polyp images and corresponding segmentation masks, manually annotated and verified by an experienced gastroenterologist. We demonstrate the use of our dataset with a traditional segmentation approach and a modern deep learning based CNN approach. This work will be valuable for researchers to reproduce results and compare their methods in the future.\&nbsp;By adding segmentation masks to the Kvasir dataset, which until today only consisted of framewise annotations, we enable multimedia and computer vision researchers to contribute in the field of polyp segmentation and automatic analysis of colonoscopy videos.\&nbsp;\&nbsp;},
	keywords = {Kvasir-SEG dataset, Medical images, Polyp segmentation, ResUNet  Fuzzy c-mean clustering, Semantic segmentation},
	author = {Jha, Debesh and Pia H. {Smedsrud} and Riegler, Michael and Halvorsen, P{\r a}l and H{\r a}vard D. {Johansen} and de Lange, Thomas and Johansen, Dag}
}
@inproceedings {27639,
	title = {LightLayers: Parameter Efficient Dense and Convolutional Layers for Image Classification},
	journal = {The Joint International Conference PDCAT-PAAP 2020},
	year = {2020},
	publisher = { Springer},
	abstract = {Deep Neural Networks (DNNs) have become the de-facto standard in computer vision, as well as in many other pattern recognition tasks. A key drawback of DNNs is that the training phase can be very computationally expensive. Organizations or individuals that cannot afford purchasing state-of-the-art hardware or tapping into cloud-hosted infrastructures may face a long waiting time before the training completes or might not be able to train a model at all. Investigating novel ways to reduce the training time could be a potential solution to alleviate this drawback, and thus enabling more rapid development of new algorithms and models. In this paper, we propose LightLayers, a method for reducing the number of trainable parameters in deep neural networks (DNN). The proposed LightLayers consists of LightDense andLightConv2D layer that are as efficient as regular Conv2D and Dense layers, but uses less parameters. We resort to Matrix Factorization to reduce the complexity of the DNN models resulting into lightweight DNNmodels that require less computational power, without much loss in the accuracy. We have tested LightLayers on MNIST, Fashion MNIST, CI-FAR 10, and CIFAR 100 datasets. Promising results are obtained for MNIST, Fashion MNIST, CIFAR-10 datasets whereas CIFAR 100 shows acceptable performance by using fewer parameters.},
	keywords = {CIFAR-10, Convolutional  neural network, Deep  Learning, Fashion MNIST, Lightweight  model, MNIST, Weight decomposition},
	author = {Jha, Debesh and Yazidi, Anis and Riegler, Michael and Johansen, Dag and H{\r a}vard D. {Johansen} and Halvorsen, P{\r a}l}
}
@inproceedings {27637,
	title = {Medico Multimedia Task at MediaEval 2020: Automatic Polyp Segmentation},
	journal = {Medico MediaEval 2020},
	year = {2020},
	publisher = {CEUR},
	abstract = {Colorectal cancer is the third most common cause of cancer worldwide. According to Global cancer statistics 2018, the incidence of colorectal cancer is increasing in both developing and developed countries. Early detection of colon anomalies such as polyps is important for cancer prevention, and automatic polyp segmentation can play a crucial role for this. Regardless of the recent advancement in early detection and treatment options, the estimated polyp miss rate is still around 20\%. Support via an automated computer-aided diagnosis system could be one of the potential solutions for the overlooked polyps. Such detection systems can help low-cost design solutions and save doctors time, which they could for example use to perform more patient examinations. In this paper, we introduce the 2020 Medico challenge, provide some information on related work and the dataset, describe the task and evaluation metrics, and discuss the necessity of organizing the Medico challenge.},
	author = {Jha, Debesh and Hicks, Steven and Emanuelsen, Krister and H{\r a}vard D. {Johansen} and Johansen, Dag and de Lange, Thomas and Riegler, Michael and Halvorsen, P{\r a}l}
}
@inproceedings {leorganiser,
	title = {Organiser Team at ImageCLEFlifelog 2020: A Baseline Approach for Moment Retrieval and Athlete Performance Prediction using Lifelog Data},
	journal = {CLEF2020},
	year = {2020},
	publisher = {CEUR Workshop Proceedings},
	author = {Le, Tu-Khiem and Ninh, Van-Tu and Zhou, Liting and Nguyen-Ngoc, Minh-Huy and Trinh, Huu-Duc and Tran, Nguyen-Hien and Piras, Luca and Riegler, Michael and Halvorsen, P{\r a}l and Lux, Mathias}
}
@inproceedings {ninh2020overview,
	title = {Overview of ImageCLEF lifelog 2020: lifelog moment retrieval and sport performance lifelog},
	journal = {CLEF2020 },
	year = {2020},
	publisher = {CEUR Workshop Proceedings},
	author = {Ninh, Van-Tu and Le, Tu-Khiem and Zhou, Liting and Piras, Luca and Riegler, Michael and Halvorsen, P{\r a}l and Tran, Minh-Triet and Lux, Mathias and Gurrin, Cathal and Dang-Nguyen, Duc-Tien}
}
@inproceedings {27644,
	title = {Overview of the ImageCLEF 2020: Multimedia Retrieval in Medical, Lifelogging, Nature, and Internet Applications},
	journal = {CLEF 2020},
	volume = {12260},
	year = {2020},
	pages = {311 - 341},
	publisher = {Springer International Publishing},
	address = {Cham},
	abstract = {This paper presents an overview of the 2020 ImageCLEF lab that will be organized as part of the Conference and Labs of the Evaluation Forum{\textemdash}CLEF Labs 2020 in Thessaloniki, Greece. ImageCLEF is an ongoing evaluation initiative (run since 2003) that promotes the evaluation of technologies for annotation, indexing and retrieval of visual data with the aim of providing information access to large collections of images in various usage scenarios and domains. In 2020, the 18th edition of ImageCLEF will organize four main tasks: (i) a\&nbsp;Lifelog\&nbsp;task (videos, images and other sources) about daily activity understanding, retrieval and summarization, (ii) a\&nbsp;Medical\&nbsp;task that groups three previous tasks (caption analysis, tuberculosis prediction, and medical visual question answering) with new data and adapted tasks, (iii) a\&nbsp;Coral\&nbsp;task about segmenting and labeling collections of coral images for 3D modeling, and a new (iv)\&nbsp;Web user interface\&nbsp;task addressing the problems of detecting and recognizing hand drawn website UIs (User Interfaces) for generating automatic code. The strong participation, with over 235 research groups registering and 63 submitting over 359 runs for the tasks in 2019 shows an important interest in this benchmarking campaign. We expect the new tasks to attract at least as many researchers for 2020.},
	isbn = {978-3-030-58218-0},
	issn = {0302-9743},
	doi = {10.1007/978-3-030-58219-710.1007/978-3-030-58219-7_22},
	url = {https://doi.org/10.1007/978-3-030-58219-7_22},
	author = {Ionescu, Bogdan and M{\"u}ller, Henning and P{\'e}teri, Renaud and Ben Abacha, Asma and Datla, Vivek and Sadid A. {Hasan} and Demner-Fushman, Dina and Kozlovski, Serge and Liauchuk, Vitali and Yashin Dicente {Cid} and Kovalev, Vassili and Pelka, Obioma and Christoph M. {Friedrich} and Alba Garc{\'\i}a Se {de Herrera} and Ninh, Van-Tu and Le, Tu-Khiem and Zhou, Liting and Piras, Luca and Riegler, Michael and Halvorsen, P{\r a}l and Tran, Minh-Triet and Lux, Mathias and Gurrin, Cathal and Dang-Nguyen, Duc-Tien and Chamberlain, Jon and Clark, Adrian and Campello, Antonio and Fichou, Dimitri and Berari, Raul and Brie, Paul and Dogariu, Mihai and Liviu Daniel {Stefan} and Mihai Gabriel {Constantin}},
	editor = {Arampatzis, Avi and Kanoulas, Evangelos and Tsikrika, Theodora and Vrochidis, Stefanos and Joho, Hideo and Lioma, Christina and Eickhoff, Carsten and N{\'e}v{\'e}ol, Aur{\'e}lie and Cappellato, Linda and Ferro, Nicola}
}
@inproceedings {27333,
	title = {PMData: a sports logging dataset},
	journal = {Proceedings of the 11th ACM Multimedia Systems Conference},
	year = {2020},
	pages = {231-236},
	publisher = {ACM},
	author = {Thambawita, Vajira and Hicks, Steven and Borgli, Hanna and H{\r a}kon Kvale {Stensland} and Jha, Debesh and Martin Kristoffer {Svensen} and Pettersen, Svein-Arne and Johansen, Dag and H{\r a}vard Dagenborg {Johansen} and Susann Dahl {Pettersen} and Nordvang, Simon and Pedersen, Sigurd and Gjerdrum, Anders and Gr{\o}nli, Tor-Morten and Per Morten {Fredriksen} and Eg, Ragnhild and Hansen, Kjeld and Fagernes, Siri and Claudi, Christine and Bi{\o}rn-Hansen, Andreas and Duc Tien Dang {Nguyen} and Kupka, Tomas and Hugo Lewi {Hammer} and Jain, Ramesh and Riegler, Michael and Halvorsen, P{\r a}l}
}
@inproceedings {27596,
	title = {PSYKOSE: A Motor Activity Database of Patients with Schizophrenia},
	journal = {2020 IEEE 33rd International Symposium on Computer-Based Medical Systems (CBMS)},
	year = {2020},
	publisher = {IEEE},
	address = {Rochester, MN, USA},
	doi = {10.1109/CBMS49503.202010.1109/CBMS49503.2020.00064},
	url = {https://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=9169740https://ieeexplore.ieee.org/document/9182896/http://xplorestaging.ieee.org/ielx7/9169740/9182790/09182896.pdf?arnumber=9182896},
	author = {Jakobsen, Petter and Garcia-Ceja, Enrique and Lena Antonsen {Stabell} and Ketil Joachim {Oedegaard} and Jan Oystein {Berle} and Thambawita, Vajira and Hicks, Steven and Halvorsen, P{\r a}l and Ole Bernt {Fasmer} and Riegler, Michael}
}
@inproceedings {27575,
	title = {Pyramid-Focus-Augmentation: Medical Image Segmentation with Step-Wise Focus},
	journal = {MediaEval 2020},
	year = {2020},
	publisher = {CEUR},
	abstract = {Segmentation of findings in the gastrointestinal tract is a challenging but also an important task which is an important building stone for sufficient automatic decision support systems. In this work, we present our solution for the Medico 2020 task, which focused on the problem of colon polyp segmentation. We present our simple but efficient idea of using an augmentation method that uses grids in a pyramid-like manner (large to small) for segmentation. Our results show that the proposed methods work as indented and can also lead to comparable results when competing with other methods.},
	author = {Thambawita, Vajira and Hicks, Steven and Halvorsen, P{\r a}l and Riegler, Michael}
}
@inproceedings {27557,
	title = {Real-Time Detection of Events in Soccer Videos using 3D Convolutional Neural Networks},
	journal = {2020 IEEE International Symposium on Multimedia (ISM)},
	year = {2020},
	publisher = {IEEE},
	abstract = {In this paper, we present an algorithm for automatically detecting events in soccer videos using 3D convolutional neural networks. The algorithm uses a sliding window approach to scan over a given video to detect events such as goals, yellow/red cards, and player substitutions. We test the method on three different datasets from SoccerNet, the Swedish\&nbsp; Allsvenskan, and the Norwegian Eliteserien. Overall, the results show that we can detect events with high recall, low latency, and accurate time estimation. The trade-off is a slightly lower precision compared to the current state-of-the-art, which has higher latency and performs better when a less accurate time estimation can be accepted. In addition to the presented algorithm, we perform an extensive ablation study on how the different parts of the training pipeline affect the final results.\&nbsp;},
	doi = {10.1109/ISM.2020.00030},
	author = {Olav A. Norg{\r a}r {Rongved} and Hicks, Steven and Thambawita, Vajira and H{\r a}kon Kvale {Stensland} and Zouganeli, Evi and Johansen, Dag and Riegler, Michael and Halvorsen, P{\r a}l}
}
@inproceedings {27612,
	title = {Scalable Infrastructure for Efficient Real-Time Sports Analytics},
	journal = {Companion Publication of the 2020 International Conference on Multimodal Interaction},
	year = {2020},
	publisher = {ACM},
	address = {New York, NY, USA},
	abstract = {Recent technological advances are adapted in sports to improve performance, avoid injuries, and make advantageous decisions. In this paper, we describe our ongoing efforts to develop and deploy PMSys, our smartphone-based athlete monitoring and reporting system. We describe our first attempts to gain insight into some of the data we have collected. Experiences so far are promising, both on the technical side and for athlete performance development. Our initial application of artificial-intelligence methods for prediction is encouraging and indicative.},
	keywords = {algorithmic analysis, artificial intelligence, Machine learning, privacy-preserving data collection, Sports performance logging},
	isbn = {9781450380027},
	doi = {10.1145/339503510.1145/3395035.3425300},
	url = {https://dl.acm.org/doi/proceedings/10.1145/3395035https://dl.acm.org/doi/10.1145/3395035.3425300https://dl.acm.org/doi/pdf/10.1145/3395035.3425300},
	author = {H{\r a}vard D. {Johansen} and Johansen, Dag and Kupka, Tomas and Riegler, Michael and Halvorsen, P{\r a}l},
	editor = {Truong, Khiet and Heylen, Dirk and Czerwinski, Mary and Berthouze, Nadia and Chetouani, Mohamed and Nakano, Mikio}
}
@inproceedings {27331,
	title = {Toadstool: A Dataset for Training Emotional IntelligentMachines Playing Super Mario Bros},
	journal = {The ACM Multimedia Systems Conference (MMSys)},
	year = {2020},
	publisher = {ACM},
	address = {The ACM Multimedia Systems Conference (MMSys)},
	abstract = {Games are often defined as engines of experience, and they are heavily relying on emotions, they arouse in players. In this paper, we present a dataset called Toadstool\&nbsp;as well as a reproducible methodology to extend on the dataset. The dataset consists of video, sensor, and demographic data collected from ten participants playing Super Mario Bros, an iconic and famous video game. The sensor data is collected through an Empatica E4 wristband, which provides high-quality measurements and is graded as a medical device. In addition to the dataset and the methodology for data collection, we present a set of baseline experiments which show that we can use video game frames together with the facial expressions to predict the blood volume pulse of the person playing Super Mario Bros. With the dataset and the collection methodology we aim to contribute to research on emotionally aware machine learning algorithms, focusing on reinforcement learning and multimodal data fusion. We believe that the presented dataset can be interesting for a manifold of researchers to explore exciting new interdisciplinary questions.\&nbsp;},
	doi = {10.1145/3339825.3394939},
	url = {https://dl.acm.org/doi/10.1145/3339825.3394939},
	author = {Svoren, Henrik and Thambawita, Vajira and Halvorsen, P{\r a}l and Jakobsen, Petter and Garcia-Ceja, Enrique and Farzan Majeed {Noori} and Hugo Lewi {Hammer} and Lux, Mathias and Riegler, Michael and Hicks, Steven}
}
@inproceedings {27576,
	title = {Vid2Pix - A Framework for Generating High-Quality Synthetic Videos},
	journal = {2020 IEEE International Symposium on Multimedia (ISM)},
	year = {2020},
	publisher = {IEEE},
	abstract = {Data is arguably the most important resource today as it fuels the algorithms powering services we use every day. However, in fields like medicine, publicly available datasets are few, and labeling medical datasets require tedious efforts from trained specialists. Generated synthetic data can be to future successful healthcare clinical intelligence. Here, we present a GAN-based video generator demonstrating promising results.},
	author = {Oda O. {Nedrejord} and Thambawita, Vajira and Hicks, Steven and Halvorsen, P{\r a}l and Riegler, Michael}
}
@inproceedings {26858,
	title = {ACM Multimedia BioMedia 2019 Grand Challenge Overview},
	journal = {The ACM International Conference on Multimedia (ACM MM)},
	year = {2019},
	month = {10/2019},
	pages = {2563-2567},
	publisher = {ACM Press},
	address = {New York, New York, USA},
	abstract = {The BioMedia 2019 ACM Multimedia Grand Challenge is the first in a series of competitions focusing on the use of multimedia for different medical use-cases. In this year{\textquoteright}s challenge, the participants are asked to develop efficient algorithms which automatically detect a variety of findings commonly identified in the gastrointestinal (GI) tract (a part of the human digestive system). The purpose of this task is to develop methods to aid medical doctors performing routine endoscopy inspections of the GI tract. In this paper, we give a detailed description of the four different tasks of this year{\textquoteright}s challenge, present the datasets used for training and testing, and discuss how each submission is evaluated both qualitatively and quantitatively.},
	isbn = {9781450368896},
	doi = {10.1145/334303110.1145/3343031.3356058},
	url = {http://dl.acm.org/citation.cfm?doid=3343031http://dl.acm.org/citation.cfm?doid=3343031.3356058http://dl.acm.org/ft_gateway.cfm?id=3356058\&ftid=2092095\&dwn=1},
	author = {Hicks, Steven and Petlund, Andreas and de Lange, Thomas and Peter Thelin {Schmidt} and Halvorsen, P{\r a}l and Riegler, Michael and Pia H. {Smedsrud} and Trine B. {Haugen} and Kristin Ranheim {Randel} and Pogorelov, Konstantin and H{\r a}kon Kvale {Stensland} and Dang-Nguyen, Duc-Tien and Lux, Mathias},
	editor = {Larson, Martha and Gravier, Guillaume and Hung, Hayley and Ngo, Chong-Wah and Wei Tsang {Ooi}}
}
@article {26455,
	title = {Automatic detection of passable roads after floods in remote sensed and social media data},
	journal = {Signal Processing: Image Communication},
	volume = {74},
	year = {2019},
	pages = {110-118},
	publisher = {Elsevier},
	abstract = {This paper addresses the problem of floods classification and floods aftermath detection based onboth social media and satellite imagery. Automatic detection of disasters such as floods is still a very challenging task. The focus lies on identifying passable routes or roads during floods. Two novel solutions are presented, which were developed for two corresponding tasks at the MediaEval 2018 benchmarking challenge. The tasks are (i) identification of images providing evidence for road passability and (ii) differentiation and detection of passable and non-passable roads in images from two complementary sources of information. For the first challenge, we mainly rely on object and scene-level features extracted through multiple deep models pre-trained on the ImageNet and Places datasets. The object and scene-level features are then combined using early, late and double fusion techniques. To identify whether or not it is possible for a vehicle to pass a road in satellite images, we rely on Convolutional Neural Networks and a transfer learning-based classification approach. The evaluation of the proposed methods is carried out on the large-scale datasets provided for the benchmark competition. The results demonstrate significant improvement in the performance over the recent state-of-art approaches.},
	keywords = {convolutional neural networks, Flood detection, Multimedia Indexing and Retrieval, Natural Disasters, Satellite Imagery, Social Media},
	doi = {https://doi.org/10.1016/j.image.2019.02.002},
	author = {Ahmad, Kashif and Pogorelov, Konstantin and Riegler, Michael and Ostroukhova, Olga and Halvorsen, P{\r a}l and Conci, Nicola and Dahyot, Rozenn}
}
@inproceedings {borgli19ISMICT,
	title = {Automatic Hyperparameter Optimization for Transfer Learning on Medical Image Datasets Using Bayesian Optimization},
	journal = {13th International Symposium on Medical Information and Communication Technology (ISMICT)},
	year = {2019},
	pages = {1-6},
	publisher = {IEEE},
	doi = {10.1109/ISMICT.2019.8743779},
	author = {Borgli, Rune and H{\r a}kon Kvale {Stensland} and Riegler, Michael and Halvorsen, P{\r a}l}
}
@article {pogorelov2019bleeding,
	title = {Bleeding detection in wireless capsule endoscopy videos{\textemdash}Color versus texture features},
	journal = {Journal of applied clinical medical physics},
	volume = {20},
	year = {2019},
	pages = {141-154},
	publisher = {Wiley Online Library},
	author = {Pogorelov, Konstantin and Suman, Shipra and Fawnizu Azmadi {Hussin} and Aamir Saeed {Malik} and Ostroukhova, Olga and Riegler, Michael and Halvorsen, P{\r a}l and Shiaw Hooi {Ho} and Goh, Khean-Lee}
}
@inbook {27154,
	title = {Challenges for Multimedia Research in E-Sports Using Counter-Strike Global Offensive as an Example},
	booktitle = {Savegame},
	volume = {4},
	year = {2019},
	pages = {197 - 206},
	publisher = {Springer Fachmedien Wiesbaden},
	organization = {Springer Fachmedien Wiesbaden},
	address = {Wiesbaden},
	abstract = {That video and computer games have reached the masses is a well-known fact. However, game streaming and, therefore, watching other people play videogames has also outgrown its humble beginnings by far. Game streams, be it live or recorded, are viewed by millions. Many of the streams are broadcasting competitive multiplayer games. This is called e-sports and it is very similar to sports broadcasting. E-sports is organized in leagues and tournaments in which players can compete in controlled environments and viewers can experience the matches, discuss and criticize just like in physical sports. In this paper, we look into the challenges for computer science in general and multimedia research in particular. The multimedia research community has done a lot of work on video streaming, broadcasting and analyzing the audience, but has missed the opportunity to investigate e-sports in detail. We focus on one particular game we deem representative for e-sports,\&nbsp;Counter-Strike: Global Offensive, and investigate how the audience consumes game streams from competitive tournaments.},
	isbn = {978-3-658-27394-1},
	issn = {2524-3241},
	doi = {10.1007/978-3-658-27395-8_13},
	url = {http://link.springer.com/10.1007/978-3-658-27395-8_13},
	author = {Lux, Mathias and Riegler, Michael and Halvorsen, P{\r a}l and Dang-Nguyen, Duc-Tien and Potthast, Martin},
	editor = {Elmenreich, Wilfried and Ren{\'e} Reinhold {Schallegger} and Schniz, Felix and Gabriel, Sonja and P{\"o}lsterl, Gerhard and Wolfgang B. {Ruge}}
}
@article {26546,
	title = {Deep Learning for Automatic Generation of Endoscopy Reports},
	journal = {Gastrointestinal Endoscopy},
	volume = {89},
	year = {2019},
	month = {06/2019},
	publisher = {Elsevier},
	address = {Gastrointestinal Endoscopy},
	doi = {10.1016/j.gie.2019.04.053},
	author = {Hicks, Steven and Pia H. {Smedsrud} and Riegler, Michael and de Lange, Thomas and Petlund, Andreas and Sigrun Losada {Eskeland} and Pogorelov, Konstantin and Peter Thelin {Schmidt} and Halvorsen, P{\r a}l}
}
@article {26631,
	title = {Efficient Live and On-Demand Tiled HEVC 360 VR Video Streaming},
	journal = {International Journal of Semantic Computing},
	volume = {13},
	number = {3},
	year = {2019},
	pages = {367-391},
	publisher = {World Scientific},
	abstract = {360\&nbsp;panorama video displayed through Virtual reality (VR) glasses or large screens o{\textregistered}ers immersive user experiences, but as such technology becomes commonplace, the need for e{\textpm}cient streaming methods of such high-bitrate videos arises. In this respect, the attention that 360panorama video has received lately is huge. Many methods have already been proposed, and in this paper, we shed more light on the di{\textregistered}erent trade-o{\textregistered}s in order to save bandwidth while preserving the video quality in the user{\textquoteright}s ̄eld-of-view (FoV). Using 360\&nbsp;VR content delivered to a Gear VR head-mounted display with a Samsung Galaxy S7 and to a Huawei Q22 set-top- box, we have tested various tiling schemes analyzing the tile layout, the tiling and encoding overheads, mechanisms for faster quality switching beyond the DASH segment boundaries and quality selection con ̄gurations. In this paper, we present an e{\textpm}cient end-to-end design and real-world implementation of such a 360\&nbsp;streaming system. Furthermore, in addition to researching an on-demand system, we also go beyond the existing on-demand solutions and present a\&nbsp;live\&nbsp;streaming system which strikes a trade-o{\textregistered} between bandwidth usage and the video quality in the user{\textquoteright}s FoV. We have created an architecture that combines RTP and DASH, and our system multiplexes a single HEVC hardware decoder to provide faster quality switching than at the traditional GOP boundaries. We demonstrate the performance and illustrate the trade-o{\textregistered}s through real-world experiments where we can report comparable bandwidth savings to existing on-demand approaches, but with faster quality switches when the FoV changes.},
	author = {Jeppsson, Mattis and Espeland, H{\r a}vard and Kupka, Tomas and Langseth, Ragnar and Petlund, Andreas and Qiaoqiao, Peng and Xue, Chuansong and Johansen, Dag and Pogorelov, Konstantin and H{\r a}kon Kvale {Stensland} and Griwodz, Carsten and Riegler, Michael and Halvorsen, P{\r a}l}
}
@misc {runeGTC2019,
	title = {Efficient Processing of Medical Videos in a Multi-auditory Environment Using Gpu Lending},
	year = {2019},
	address = {NVIDIA{\textquoteright}s GPU Technology Conference (GTC)},
	author = {Borgli, Rune and Pogorelov, Konstantin and Riegler, Michael and Markussen, Jonas and H{\r a}kon Kvale {Stensland} and Halvorsen, P{\r a}l and Griwodz, Carsten and Sigrun Losadal {Eskeland} and de Lange, Thomas}
}
@inproceedings {26923,
	title = {Extracting temporal features into a spatial domain using autoencoders for sperm video analysis},
	journal = {MediaEval 2019},
	year = {2019},
	month = {10/2019},
	publisher = {CEUR Workshop Proceedings},
	abstract = {In this paper, we present a two-step deep learning method that is used to predict sperm motility and morphology based on video recordings of human spermatozoa. First, we use an autoencoder to extract temporal features from a given semen video and plot these into image-space, which we call feature-images. Second, these feature-images are used to perform transfer learning to predict the motility and morphology values of human sperm. The presented method shows it{\textquoteright}s capability to extract temporal information into spatial domain feature-images which can be used with traditional convolutional neural networks. Furthermore, the accuracy of the predicted motility of a given semen sample shows that a deep learning-based model can capture the temporal information of microscopic recordings of human semen.},
	author = {Thambawita, Vajira and Halvorsen, P{\r a}l and Hugo Lewi {Hammer} and Riegler, Michael and Trine B. {Haugen}}
}
@article {26754,
	title = {Flexible device compositions and dynamic resource sharing in PCIe interconnected clusters using Device Lending},
	journal = {Cluster Computing},
	volume = {22},
	year = {2019},
	month = {09/2019},
	pages = {1-24},
	publisher = { Springer},
	abstract = {Modern workloads often exceed the processing and I/O capabilities provided by resource virtualization, requiring direct access to the physical hardware in order to reduce latency and computing overhead. For computers interconnected in a cluster, access to remote hardware resources often requires facilitation both in hardware and specialized drivers with virtualization support. This limits the availability of resources to specific devices and drivers that are supported by the virtualization technology being used, as well as what the interconnection technology supports. For PCI Express (PCIe) clusters, we have previously proposed Device Lending as a solution for enabling direct low latency access to remote devices. The method has extremely low computing overhead and does not require any application- or device-specific distribution mechanisms. Any PCIe device, such as network cards disks, and GPUs, can easily be shared among the connected hosts. In this work, we have extended our solution with support for a virtual machine (VM) hypervisor. Physical remote devices can be {\textquotedblleft}passed through{\textquotedblright} to VM guests, enabling direct access to physical resources while still retaining the flexibility of virtualization. Additionally, we have also implemented multi-device support, enabling shortest-path peer-to-peer transfers between remote devices residing in different hosts. Our experimental results prove that multiple remote devices can be used, achieving bandwidth and latency close to native PCIe, and without requiring any additional support in device drivers. I/O intensive workloads run seamlessly using both local and remote resources. With our added VM and multi-device support, Device Lending offers highly customizable configurations of remote devices that can be dynamically reassigned and shared to optimize resource utilization, thus enabling a flexible composable I/O infrastructure for VMs as well as bare-metal machines.},
	issn = {1573-7543},
	doi = {10.1007/s10586-019-02988-0},
	url = {https://link.springer.com/article/10.1007/s10586-019-02988-0},
	author = {Markussen, Jonas and Lars Bj{\o}rlykke {Kristiansen} and Borgli, Rune and H{\r a}kon Kvale {Stensland} and Seifert, Friedrich and Riegler, Michael and Griwodz, Carsten and Halvorsen, P{\r a}l}
}
@inproceedings {27106,
	title = {GameStory Task at MediaEval 2019},
	journal = {Proceedings of MediaEval 2019},
	year = {2019},
	month = {10/2019},
	publisher = {CEUR Workshop Proceedings (CEUR-WS.org)},
	abstract = {Game video streams are watched by millions, so that, meanwhile, one can make a living from broadcasting and commenting video games, whereas some have become professional e-sports athletes. E-sports leagues and tournaments have emerged worldwide, where players compete in controlled environments, streaming the matches online, and allowing the audience to discuss and criticize the game- play. In the GameStory task, held for the second time at MediaEval, we foster research into this exciting domain. Our focus is on an- alyzing and summarizing video game streams. With the help of\&nbsp;ZNIPE.tv, we compiled a high-quality dataset of a\&nbsp;Counter-Strike: Global Offensive\&nbsp;tournament alongside ground truth labels for two analysis tasks, forming a basis for summarization.},
	author = {Lux, Mathias and Riegler, Michael and Dang-Nguyen, Duc-Tien and Pirker, Johanna and Potthast, Martin and Halvorsen, P{\r a}l}
}
@inproceedings {26689,
	title = {GANEx: A complete pipeline of training, inference and benchmarking GAN experiments},
	journal = {2019 International Conference on Content-Based Multimedia Indexing (CBMI)},
	year = {2019},
	pages = {1-4},
	publisher = {IEEE},
	keywords = {GAN, GANEx, Generative Adversarial Network},
	author = {Thambawita, Vajira and Hugo Lewi {Hammer} and Riegler, Michael and Halvorsen, P{\r a}l}
}
@inbook {26709,
	title = {Image Retrieval Evaluation in Specific Domains},
	booktitle = {Information Retrieval Evaluation in a Changing World - Lessons Learned from 20 Years of CLEF},
	volume = {INRE, volume 41},
	year = {2019},
	pages = {275-305},
	publisher = { Springer},
	organization = { Springer},
	abstract = {Image retrieval was, and still is, a hot topic in research. It comes with many challenges that changed over the years with the emergence of more advanced methods for analysis and enormous growth of images created, shared and consumed. This chapter gives an overview of domain-specific image retrieval evaluation approaches, which were part of the ImageCLEF evaluation campaign . Specifically, the robot vision, photo retrieval, scalable image annotation and lifelogging tasks are presented. The ImageCLEF medical activity is described in a separate chapter in this volume. Some of the presented tasks have been available for several years, whereas others are quite new (like lifelogging). This mix of new and old topics has been chosen to give the reader an idea about the development and trends within image retrieval. For each of the tasks, the datasets, participants, techniques used and lessons learned are presented and discussed leading to a comprehensive summary.},
	doi = {https://doi.org/10.1007/978-3-030-22948-1_12},
	author = {Piras, Luca and Caputo, Barbara and Dang-Nguyen, Duc-Tien and Riegler, Michael and Halvorsen, P{\r a}l},
	editor = {Ferro, Nicola and Peters, Carol}
}
@misc {26509,
	title = {Kunstig intelligens for endoskopi {\textendash} Automatisk deteksjon av lesjoner i sanntid},
	year = {2019},
	publisher = {Norsk Gastroenterologisk Forening},
	address = {NGF Nytt, Vol. 26, No 1, March 2019, p. 34},
	abstract = {BAKGRUNN: I krysningspunktet mellom matematikk, informatikk og statistikk finner vi den vitenskapelige disiplinen kunstig intelligens (KI). Sammen med de siste {\r a}rs eksplosive utvikling innen teknologi har KI muliggjort nye algoritmer, modeller og systemer for maskinassistert diagnostikk. Resultater fra KI basert p{\r a} dype nevrale nettverk har vist spesielt stort potensiale, ogs{\r a} for automatisk deteksjon av lesjoner og anatomiske landemerker i gastrointestinaltraktus under endoskopi. Med sensitivitet og spesifisitet for deteksjon av polypper i tykktarmp{\r a} over 90\% m{\o}ter slike metoder n{\o}dvendige kliniske krav, men mange eksperimenter er utf{\o}rt p{\r a} begrensede datasett, eller analysert p{\r a} feilaktig grunnlag grunnet manglende tilgang og forst{\r a}else hos informatikere. For {\r a} oppn{\r a} best mulig resultat eret interdisiplin{\ae}rt samarbeid mellom klinikere og informatikereen forutsetning. Informatikerne trenger medisinske innspill for {\r a} lage effektive systemer som fungerer ute i klinikken, og klinikerne trenger forst{\r a}else av systemet for {\r a} kunne stole p{\r a} resultatet og stille p{\r a}litelige diagnoser. En stor utfordring for denne tilliten erat fremgangsm{\r a}ten til en KI-algoritme sees p{\r a} som en svart boks hvor ingen n{\o}yaktig kan dechiffrere hvordan systemet kom fremtil sin konklusjon.METODE: Vi har gjennom mange {\r a}r samlet en stor bilde- database fra endoskopier utf{\o}rt ved B{\ae}rum Sykehus, Vestre Viken HF. Bildene er gjennomg{\r a}tt og annotert av tre erfarne endoskop{\o}rer og fordelt p{\r a} 16 klasser, inkludert normal Z-linje, {\o}sofagitt, normal c{\o}kum, polypper og ulcer{\o}s colitt. Deretter er bildene brukt til {\r a} utvikle, trene og teste KI-modeller. Modellene er basert p{\r a} maskinl{\ae}ring og dyp l{\ae}ring, en gren innen KI. Med v{\r a}rt system Mimir, som kombinerer KI med informasjonss{\o}k og-gjenfinning, s{\o}ker vi {\r a} lage et helhetlig beslutningsst{\o}ttesystem for endoskop{\o}rer. Algoritmene analyserer videoer i sanntid, finner lesjoner, klassifiserer disse og gir skop{\o}ren live feedback om funn under unders{\o}kelsen, slik at funnene kan unders{\o}kes n{\ae}rmere. Mimir presenterer deretter resultatene i egen programvare, og bruker blant annet {\textquotedblleft}heatmaps{\textquotedblright} til {\r a} forklare hvordan konklusjonen er n{\r a}dd, og er p{\r a} den m{\r a}ten et bidrag p{\r a} veien til {\r a} forst{\r a} hvordan KI-algoritmene fungerer. Videre jobber vi med {\r a} videreutvikle Mimirs st{\o}tte for automatisk rapportgenerering, med bilderog standardtekst basert p{\r a} funn fra unders{\o}kelsen.RESULTATER: Deteksjon og klassifisering for de 16 gruppene har vist en sensitivitet p{\r a} 0,939 og en spesifisitet p{\r a} 0,996. Algoritmene v{\r a}re klarer {\r a} prosessere bildene i hastigheter p{\r a} mellom 30 - 1000 bilder per sekund, raskt nok til {\r a} kj{\o}re deteksjon i sanntid. En prototype av systemet er i samr{\r a}d med klinikere testet ved {\r a} koble til et koloskopisystem ute i klinikken, og kann{\r a} analysere videoer i sanntid.KONKLUSJON: Tester av v{\r a}re system viser at KI kan bli et viktig hjelpemiddel for {\r a} bedre oppdage GI-forandringer, og generere automatiske rapporter i l{\o}pet av n{\ae}rmeste fremtid. Dette kan fungere som viktig beslutningsst{\o}tte for endoskop{\o}rer, og kan brukes i oppl{\ae}ring av nye endoskop{\o}rer. Den st{\o}rste begrensningen med KI er at vi per i dag ikke vet hvordan systemet kommer frem til sin konklusjon, som kan p{\r a}virke i hvor stor grad vi stoler p{\r a} resultatet. Vi arbeider derfor med et helhetlig system som ikke bare hjelper legen med diagnostikk, men ogs{\r a} forklarer hvordan konklusjonen er n{\r a}dd, samt {\r a} generere automatiske rapporter fra unders{\o}kelsen.},
	author = {Pia H. {Smedsrud} and Riegler, Michael and de Lange, Thomas and Petlund, Andreas and Sigrun Losada {Eskeland} and Halvorsen, P{\r a}l}
}
@article {26926,
	title = {Machine Learning-Based Analysis of Sperm Videos and Participant Data for Male Fertility Prediction},
	journal = {Nature Scientific Reports },
	volume = {9},
	number = {16770},
	year = {2019},
	publisher = {Springer Nature},
	abstract = {Methods for automatic analysis of clinical data are usually targeted towards a specific modality and do not make use of all relevant data available. In the field of male human reproduction, clinical and biological dataare not used to its fullest potential. Manual evaluation of a semen sample using a microscope is time-consuming and requires extensive training. Furthermore, the validity of manual semen analysis has been questioned due to limited reproducibility, and often high inter-personnel variation. The existing computer-aided sperm analyzer systems are not recommended for routine clinical use due to methodological challenges caused by the consistency of the semen sample. Thus, there is a need for an improved methodology.We use modern and classical machine learning techniques together with a dataset consisting of\&nbsp;85\&nbsp;videos of human semen samples and related participant data to automatically predict sperm motility. Used techniques include simple linear regression and more sophisticated methods using convolutional neural networks. Our results indicate that sperm motility prediction based on deep learning using sperm motility videos is rapid to perform and consistent. The algorithms performed worse when participant data was added. In conclusion, machine learning-based automatic analysis may become a valuable tool in male infertility investigation and research.},
	author = {Hicks, Steven and Jorunn M. {Andersen} and Witczak, Oliwia and Thambawita, Vajira and Halvorsen, P{\r a}l and Hugo Lewi {Hammer} and Trine B. {Haugen} and Riegler, Michael}
}
@article {26857,
	title = {Maskinl{\ae}ringssystemer for gastrointestinale endoskopier},
	journal = {Best Practice Nordic - Gastroenterologi},
	year = {2019},
	month = {07/2019},
	publisher = {BestPracticeNordic},
	abstract = {Assistert diagnostikk med hjelp av kunstig intelligens (KI) har v{\ae}rt etterspurt lenge og kan bli et viktig hjelpemiddel innen medisin, godt hjulpet av den raske utviklingen innen maskinvare. Denne har gjort innf{\o}ringen av slike hjelpemidler mulig p{\r a} relativt kort sikt. Sikrere p{\r a}visning og klassifisering av funn og lesjoner innen radiologi og endoskopi er i ferd med {\r a} bli et viktig forskningsomr{\r a}de innen KI, og det fokuseres spesielt p{\r a} maskinl{\ae}ring. Imidlertid krever vellykket utvikling et komplett system som kan brukes i sanntid i daglig praksis, og som begrenser seg til utvikling av algoritmer. Det kreves ogs{\r a} store randomiserte studier for {\r a} fastsl{\r a} om kvaliteten og p{\r a}liteligheten til systemene er god. Vi deler i denne artikkelen v{\r a}re erfaringer fra utviklingen av et system for gastrointestinale endoskopier\&nbsp;og belyser viktige utfordringer for {\r a} skape en effektiv digital assistent.},
	url = {https://bestprac.no/maskinlaeringssystemer-for-gastrointestinale-endoskopier/},
	author = {Riegler, Michael and Pia H. {Smedsrud} and de Lange, Thomas and Halvorsen, P{\r a}l}
}
@inproceedings {26859,
	title = {Medical Multimedia Systems and Applications},
	journal = {Proceedings of the 27th ACM International Conference on Multimedia  - MM {\textquoteright}19},
	year = {2019},
	month = {1072019},
	pages = {2711-2713},
	publisher = {ACM Press},
	address = {New York, NY, USA},
	abstract = {In recent years, we have observed a rise of interest in the multimedia community towards research topics related to health. It can be observed that this goes into two interesting directions. One is personal health with a larger focus on well-being and everyday healthy living. The other direction focuses more on multimedia challenges within the health-care systems, for example, how can multimedia content produced in hospitals be used efficiently but also on the user perspective of patients and health-care personal. Challenges and requirements in this interesting and challenging direction are similar to classic multimedia research, but with some additional pitfalls and challenges. This tutorial aims to give a general introduction to the research area; to provide an overview of specific requirements, pitfalls and challenges; to discuss existing and possible future work; and to elaborate on how machine learning approaches can help in multimedia-related challenges to improve the health-care quality for patients and support medical experts in their daily work.},
	isbn = {9781450368896},
	doi = {https://doi.org/10.1145/3343031.3351319},
	url = {http://dl.acm.org/citation.cfm?doid=3343031http://dl.acm.org/citation.cfm?doid=3343031.3351319http://dl.acm.org/ft_gateway.cfm?id=3351319\&ftid=2091902\&dwn=1},
	author = {Halvorsen, P{\r a}l and Riegler, Michael and Schoeffmann, Klaus},
	editor = {Amsaleg, Laurent and Huet, Benoit and Larson, Martha and Gravier, Guillaume and Hung, Hayley and Ngo, Chong-Wah and Wei Tsang {Ooi}}
}
@inproceedings {26931,
	title = {Medico Multimedia Task at MediaEval 2019},
	journal = {MediaEval},
	year = {2019},
	publisher = {CEUR Workshop Proceedings},
	abstract = {The Medico: Multimedia for Medicine Task\&nbsp;is running for the third time as part of MediaEval 2019. This year, we have changed the task from anomaly detection in images of the gastrointestinal tract to focus on the automatic prediction of human semen quality based on videos. The purpose of this task is to aid in the assessment of male reproductive health by providing a quick and consisted method of analyzing human semen. In this paper, we describe the task in detail, give a brief description of the provided dataset, and discuss the evaluation process and the metrics used to rank the submissions of the participants.},
	author = {Hicks, Steven and Halvorsen, P{\r a}l and Trine B. {Haugen} and Jorunn M. {Andersen} and Witczak, Oliwia and Pogorelov, Konstantin and Hugo Lewi {Hammer} and Dang-Nguyen, Duc-Tien and Lux, Mathias and Riegler, Michael}
}
@inproceedings {26860,
	title = {One-Dimensional Convolutional Neural Networks on Motor Activity Measurements in Detection of Depression},
	journal = {Proceedings of the 4th International Workshop on Multimedia for Personal Health \& Health Care  - HealthMedia {\textquoteright}19},
	year = {2019},
	month = {10/2019},
	pages = {9-15},
	publisher = {ACM Press},
	address = {New York, NY, USA},
	abstract = {Nowadays, it has become possible to measure different human activities using wearable devices. Besides measuring the number of daily steps or calories burned, these datasets have much more potential since different activity levels are also collected. Such data would be helpful in the field of psychology because it can relate to various mental health issues such as changes in mood and stress. In this paper, we present a machine learning approach to detect depression using a dataset with motor activity recordings of one group of people with depression and one group without, i.e., the condition group includes 23 unipolar and bipolar persons, and the control group includes 32 persons without depression. We use convolutional neural networks to classify the depressed and nondepressed patients. Moreover, different levels of depression were classified. Finally, we trained a model that predicts Montgomery{\r A}sberg Depression Rating Scale scores. We achieved an average F1-score of 0.70 for detecting the control and condition groups. The mean squared error for score prediction was approximately 4.0.\&nbsp;},
	isbn = {9781450369145},
	doi = {10.1145/334744410.1145/3347444.3356238},
	url = {http://dl.acm.org/citation.cfm?doid=3347444http://dl.acm.org/citation.cfm?doid=3347444.3356238http://dl.acm.org/ft_gateway.cfm?id=3356238\&ftid=2091091\&dwn=1},
	author = {Joakim Ihle {Frogner} and Farzan Majeed {Noori} and Halvorsen, P{\r a}l and Hicks, Steven and Garcia-Ceja, Enrique and Torresen, Jim and Riegler, Michael},
	editor = {Boll, Susanne and Lee, Jeannie and Meyer, Jochen and Nag, Nitish and Noel E. {O{\textquoteright}Connor}}
}
@inproceedings {26589,
	title = {Performance of Data Enhancements and Training Optimization for Neural Network {\textendash} A Polyp Detection Case Study},
	journal = {IEEE CBMS International Symposium on Computer-Based Medical Systems (CBMS)},
	year = {2019},
	publisher = { IEEE},
	abstract = {Deep learning using neural networks is becoming more and more popular. It is frequently used in areas like video analysis, image retrieval, traffic forecast and speech recognition. In this respect, the learning and training process usually requires a lot of data. However, in many areas, data is scarce which is definitely the case in our medical application scenario, i.e., polyp detection in the gastrointestinal tract. Here, colorectal cancer is on the list of most common cancer types, and often, the cancer arises from benign, adenomatous polyps containing dysplastic cells. Detection and removal of polyps can therefore prevent the development of cancer. Due to high cost, time consumption, patient discomfort and in-accuracy of existing procedures, researchers have started to explore systems for automatic polyp detection to assist and automate current examination procedures. Following the current gained traction for neural networks, and the typical lack of medical data, we explore how data enhancements affect the training and evaluation of the networks in terms of polyp detection accuracy and particularly if it can be used to increase the detection rate. We also experiment with how various training techniques can be used to increase performance. Our experimental results show how data enhancement and training optimization can be used to increase different aspects of the performance, but we also point out mechanisms that have no and even a negative effect.},
	author = {Fredrik Lund {Henriksen} and Jensen, Rune and H{\r a}kon Kvale {Stensland} and Johansen, Dag and Riegler, Michael and Halvorsen, P{\r a}l}
}
@inproceedings {26630,
	title = {Predicting Peek Readiness-to-Train of Soccer Players Using Long Short-Term Memory Recurrent Neural Networks},
	journal = {2019 International Conference on Content-Based Multimedia Indexing (CBMI)},
	year = {2019},
	publisher = {IEEE},
	abstract = {We are witnessing the emergence of a myriad of hardware and software systems that quantifies sport and physical activities. These are frequently touted as game changers and important for future sport developments. The vast amount of generated data is often visualized in graphs and dashboards, for use by coaches and other sports professionals to make decisions on training and match strategies. Modern machine- learning methods have the potential to further fuel this process by deriving useful insights that are not easily observable in the raw data streams.This paper tackles the problem of deriving peaks in soccer players{\textquoteright} ability to perform from subjective self-reported wellness data collected using the PMSys system. For this, we train a long short-term memory recurrent neural network model using data from two professional Norwegian soccer teams. We show that our model can predict performance peaks in most scenarios with a precision and recall of at least 90\%. Equipped with such insight, coaches and trainers can better plan individual and team training sessions, and perhaps avoid over training and injuries.},
	doi = {10.1109/CBMI.2019.8877406},
	author = {Wiik, Theodor and H{\r a}vard D {Johansen} and Svein Arne {Pettersen} and Baptista, Ivan and Kupka, Tomas and Johansen, Dag and Riegler, Michael and Halvorsen, P{\r a}l}
}
@inproceedings {26929,
	title = {Predicting Sperm Motility and Morphology using Deep Learning and Handcrafted Features},
	journal = {MediaEval},
	year = {2019},
	publisher = {ceur ws org},
	abstract = {This paper presents the approach proposed by the organizer team (SimulaMet) for MediaEval 2019 Multimedia for Medicine: The Medico Task. The approach uses a data preparation method which is based on global features extracted from multiple frames within each video and then combines this with information about the patient in order to create a compressed representation of each video. The goal is to create a less hardware expensive data representation that still retains the temporal information of the video and related patient data. Overall, the results need some improvement before being a viable option for clinical use.},
	author = {Hicks, Steven and Halvorsen, P{\r a}l and Trine B. {Haugen} and Jorunn M. {Andersen} and Witczak, Oliwia and Pogorelov, Konstantin and Hugo Lewi {Hammer} and Dang-Nguyen, Duc-Tien and Lux, Mathias and Riegler, Michael}
}
@inproceedings {26629,
	title = {Real-time Analysis of Physical Performance Parameters in Elite Soccer},
	journal = {2019 International Conference on Content-Based Multimedia Indexing (CBMI)},
	year = {2019},
	publisher = { IEEE},
	abstract = {Technology is having vast impact on the sports in- dustry, and in particular soccer. All over the world, soccer teams are adapting digital information systems to quantify performance metrics. The goal is to assess strengths and weaknesses of indi- vidual players, training regimes, and play strategies; to improve performance and win games. However, most existing methods rely on post-game analytic. This limits coaches to review games in retrospect without any means to do changes during sessions. In collaboration with an elite soccer club, we have developed Metrix which is a computerized toolkit for coaches to perform real- time monitoring and analysis of the players{\textquoteright} performance. Using sensor technology to track movement, performance parameters are instantly available to coaches through a mobile phone client. Metrix provides coaches with a toolkit to individualize training load to different playing positions on the field, or to the player himself. Our results show that Metrix is able to quantify player performance and propagate it to coaches in real-time during a match or practice, i.e., latency is below 100 ms on the field. In our initial user evaluation, the coaches express that this is a valuable asset in day-to-day work.},
	doi = {10.1109/CBMI.2019.8877422},
	author = {Andreassen, Kim and Johansen, Dag and Johansen, H{\r a}vard and Baptista, Ivan and Svein Arne {Pettersen} and Riegler, Michael and Halvorsen, P{\r a}l}
}
@inproceedings {26812,
	title = {ResUNet++: An Advanced Architecture for Medical Image Segmentation},
	journal = {2019 IEEE International Symposium on Multimedia (ISM)},
	year = {2019},
	publisher = {IEEE},
	address = {San Diego, California, USA},
	abstract = {Accurate computer-aided polyp detection and segmentation during colonoscopy examinations can help endoscopists resect abnormal tissue and thereby decrease chances of polyps growing into cancer. Towards developing a fully automated model for pixel-wise polyp segmentation, we propose ResUNet++, which is an improved ResUNet architecture for colonoscopic image segmentation. Our experimental evaluations show that the suggested architecture produces good segmentation results on publicly available datasets. Furthermore, ResUNet++ significantly outperforms U-Net and ResUNet, two key state-of-the-art deep learning architectures, by achieving high evaluation scores with a dice coefficient of 81.33\%, and a mean Intersection over Union (mIoU) of 79.27\% for the Kvasir-SEG dataset and a dice coefficient of 79.55\%, and a mIoU of 79.62\% with CVC-612 dataset.},
	keywords = {colonoscopy, deep learning, health informatics, Medical image segmentation, Polyp segmentation, Semantic segmentation},
	author = {Jha, Debesh and Pia H. {Smedsrud} and Riegler, Michael and Johansen, Dag and de Lange, Thomas and Halvorsen, P{\r a}l and H{\r a}vard D {Johansen}}
}
@inproceedings {26820,
	title = {Saga: An Open Source Platform for Training Machine Learning Models and Community-driven Sharing of Techniques},
	journal = {International Conference on Content-Based Multimedia Indexing (CBMI 2019)},
	year = {2019},
	pages = {1-4},
	publisher = {IEEE},
	doi = {10.1109/CBMI.2019.8877455},
	author = {Borgli, Hanna and H{\r a}kon Kvale {Stensland} and Halvorsen, P{\r a}l and Riegler, Michael}
}
@inproceedings {26708,
	title = {Semantic Analysis of Soccer News for Automatic Game Event Classification},
	journal = {2019 International Conference on Content-Based Multimedia Indexing (CBMI)},
	year = {2019},
	publisher = {IEEE},
	abstract = {We are today overwhelmed with information, of which an important part is news. Sports news, in particular, has become very popular, where soccer makes up a big part of this coverage. For sports fans, it can be a time consuming and tedious to keep up with the news that they really care about. In this paper, we present different machine learning methods applied to soccer news from a Norwegian newspaper and a TV station{\textquoteright}s news site to summarize the content in a short and digestible manner. We present a system to collect, index, label, analyze, and present the collected news articles based on the content. We perform a thorough comparison between deep learning and traditional machine learning algorithms on text classification. Furthermore, we present a dataset of soccer news which was collected from two different Norwegian news sites and shared online.\&nbsp;},
	author = {Nordskog, Aanund and Halvorsen, P{\r a}l and Hicks, Steven and H{\r a}kon Kvale {Stensland} and Hugo Lewi {Hammer} and Johansen, Dag and Riegler, Michael}
}
@article {ahmad2019social,
	title = {Social media and satellites: Disaster event detection, linking and summarization},
	journal = {Multimedia Tools and Applications},
	volume = {78},
	number = {3},
	year = {2019},
	pages = {2837{\textendash}2875},
	publisher = {Springer},
	address = {Netherlands},
	author = {Ahmad, Kashif and Pogorelov, Konstantin and Riegler, Michael and Conci, Nicola and Halvorsen, P{\r a}l}
}
@inproceedings {26922,
	title = {Stacked dense optical flows and dropout layers to predict sperm motility and morphology},
	journal = {MediaEval 2019, 27-29 October 2019, Sophia Antipolis, France},
	year = {2019},
	month = {10/2019},
	abstract = {In this paper, we analyse two deep learning methods to predict sperm motility and sperm morphology from sperm videos. We use two different inputs: stacked pure frames of videos and dense optical flows of video frames. To solve this regression task of predicting motility and morphology, stacked dense optical flows and extracted original frames from sperm videos were used with the modified state of the art convolution neural networks. For modifications of the selected models, we have introduced an additional multi-layer perceptron to overcome the problem of over-fitting. The method which had an additional multi-layer perceptron with dropout layers, shows the best results when the inputs consist of both dense optical flows and an original frame of videos.},
	author = {Thambawita, Vajira and Halvorsen, P{\r a}l and Hugo Lewi {Hammer} and Riegler, Michael and Trine B. {Haugen}}
}
@inproceedings {26587,
	title = {Summarizing E-Sports Matches and Tournaments: The Example of Counter-Strike: Global Offensive},
	journal = {International Workshop on Immersive Mixed and Virtual Environment Systems (MMVE)},
	year = {2019},
	publisher = {ACM},
	abstract = {That video and computer games have reached the masses is a well known fact. Furthermore, game streaming and watching other people play video games is another phenomenon that has outgrown its small beginning by far, and game streams, be it live or recorded, are today viewed by millions. E-sports is the result of organized leagues and tournaments in which players can compete in controlled environments and viewers can experience the matches, discuss and criticize, just like in physical sports. \&nbsp;However, as traditional sports, e-sports matches may be long and contain less interesting parts, introducing the challenge of producing well directed summaries and highlights.\&nbsp;In this paper, we describe our efforts to approach the game streaming and e-sports phenomena from a multimedia research point of view. We focus on the challenge of summarizing matches from specific relevant game, Counter-Strike: Global Offensive (CS:GO). We survey related work, describe the rules and structure of the game and identify the main challenges for summarizing e-sports matches. With this contribution, we aim to foster multimedia research in the area of e-sports and game streaming.},
	author = {Lux, Mathias and Halvorsen, P{\r a}l and Dang-Nguyen, Duc-Tien and H{\r a}kon Kvale {Stensland} and Kesavulu, Manoj and Potthast, Martin and Riegler, Michael}
}
@inproceedings {26547,
	title = {Unsupervised Preprocessing to Improve Generalisation for Medical Image Classification},
	journal = {IEEE 13th International Symposium on Medical Information and Communication Technology (ISMICT)},
	year = {2019},
	publisher = { IEEE},
	abstract = {Automated disease detection in videos and images from the gastrointestinal (GI) tract has received much attention in the last years. However, the quality of image data is often reduced due to overlays of text and positional data.\&nbsp;In this paper, we present different methods of preprocessing such images and we describe our approach to GI disease classification for the Kvasir v2 dataset.\&nbsp;We propose multiple approaches to inpaint problematic areas in the images to improve the anomaly classification, and we discuss the effect that such preprocessing does to the input data.In short, our experiments show that the proposed methods improve the Matthews correlation coefficient by approximately 7\% in terms of better classification of GI anomalies.},
	doi = {10.1109/ISMICT.2019.8743979},
	author = {Kirker{\o}d, Mathias and Borgli, Rune and Thambawita, Vajira and Hicks, Steven and Riegler, Michael and Halvorsen, P{\r a}l}
}
@inproceedings {26928,
	title = {Using 2D and 3D Convolutional Neural Networks to Predict Semen Quality},
	journal = {MediaEval},
	year = {2019},
	publisher = {CEUR Workshop Proceedings},
	abstract = {In this paper, we present the approach of team Jmag\&nbsp;to solve this year{\textquoteright}s Medico Multimedia Task as part of the MediaEval 2019 Benchmark. This year, the task focuses on automatically determining quality characteristics of human sperm through the analysis of microscopic videos of human semen and associated patient data. Our approach is based on deep convolutional neural networks (CNNs) of varying sizes and dimensions. Here, we aim to analyze both the spatial and temporal information present in the videos. The results show that the method holds promise for predicting the motility of sperm, but predicting morphology appears to be more difficult.},
	author = {Rosenblad, Jon-Magnus and Hicks, Steven and H{\r a}kon Kvale {Stensland} and Trine B. {Haugen} and Halvorsen, P{\r a}l and Riegler, Michael}
}
@inproceedings {26930,
	title = {Using Deep Learning to Predict Motility and Morphology of Human Sperm},
	journal = {MediaEval 2019},
	year = {2019},
	publisher = {CEUR Workshop Proceedings},
	abstract = {In the Medico Task 2019, the main focus is to predict sperm quality based on videos and other related data. In this paper, we present the approach of team LesCats\&nbsp;which is based on deep convolution neural networks, where we experiment with different data preprocessing methods to predict the morphology and motility of human sperm. The achieved results show that deep learning is a promising method for human sperm analysis. Out best method achieves a mean absolute error of 8.962\&nbsp;for the motility task and a mean absolute error of 5.303\&nbsp;for the morphology task.},
	author = {Hicks, Steven and Trine B. {Haugen} and Halvorsen, P{\r a}l and Riegler, Michael}
}
@inproceedings {haugen2019visem,
	title = {VISEM: a multimodal video dataset of human spermatozoa},
	journal = {Proceedings of the 10th ACM Multimedia Systems Conference},
	year = {2019},
	pages = {261{\textendash}266},
	publisher = {ACM},
	author = {Trine B {Haugen} and Hicks, Steven and Jorunn M {Andersen} and Witczak, Oliwia and Hugo Lewi {Hammer} and Borgli, Rune and Halvorsen, P{\r a}l and Riegler, Michael},
	editor = {Zink, Michael}
}
@inproceedings {26927,
	title = {A Web-Based Software for Training and Quality Assessment in the Image Analysis Workflow for Cardiac T1 Mapping MRI},
	journal = {2019 IEEE International Symposium on Multimedia (ISM)},
	year = {2019},
	publisher = {IEEE},
	abstract = {Medical practice makes significant use of imaging scans such as Ultrasound or MRI as a diagnostic tool. They are used in the visual inspection or quantification of medical parameters computed from the images in post-processing. However, the value of such parameters depends much on the user{\textquoteright}s variability, device, and algorithmic differences. In this paper, we focus on quantifying the variability due to the human factor, which can be primarily addressed by the structured training of a human operator. We focus on a specific emerging cardiovascular \gls{mri} methodology, the T1 mapping, that has proven useful to identify a range of pathological alterations of the myocardial tissue structure. Training, especially in emerging techniques, is typically not standardized, varying dramatically across medical centers and research teams. Additionally, training assessment is mostly based on qualitative approaches. Our work aims to provide a software tool combining traditional clinical metrics and convolutional neural networks to aid the training process by gathering contours from multiple trainees, quantifying discrepancy from local gold standard or standardized guidelines, classifying trainees output based on critical parameters that affect contours variability.},
	doi = {10.1109/ISM46123.2019.00047},
	author = {Edvarda Regine {Eriksen} and Hicks, Steven and Riegler, Michael and Halvorsen, P{\r a}l and Carapella, Valentina}
}
@inproceedings {26273,
	title = {The 2018 Medico Multimedia Task Submission of Team NOAT using Neural Network Features and Search-based Classification},
	journal = {Proceeding of the MediaEval Benchmarking Initiative for Multimedia Evaluation},
	year = {2018},
	month = {10/2018},
	publisher = {CEUR Workshop Proceedings},
	abstract = {In this paper, we describe our approach for the classification of medical images depicting the human gastrointestinal tract. Search-based classification is performed in three stages. In the first stage, we extract deep features for each image using pre-trained deep-learning models. In the second stage, we use LIRE \&nbsp;to index the generated features, so that we can then, in the final stage, search the index for similar images and make our predictions based on the results. With this approach, we achieved a MCC score of 0,54\&nbsp;and a accuracy of 0,94, which shows that deep features combined with search-based classification are a viable option for medical image analysis.\&nbsp;\&nbsp;},
	author = {Steiner, Michael and Lux, Mathias and Halvorsen, P{\r a}l}
}
@misc {25795,
	title = {Automatic Detection of Angiectasia: Evaluation of Deep Learning and Handcrafted Approaches},
	howpublished = { IEEE Conference on Biomedical and Health Informatics (BHI) 2018},
	year = {2018},
	abstract = {Angiectasia, formerly called angiodysplasia, is one of the most frequent vascular lesions and often the cause of gastrointestinal bleedings. Medical specialists assessing videos of examinations reach a detection performance of 16\% for the detection of bleeding to 69\% for the detection of angiectasia. In this paper, we present several machine-learning-based approaches for angiectasia detection in wireless video capsule endoscopy images. The most promising results for pixel-wise localization and frame-wise detection are obtained by the proposed deep learning approach using generative adversarial networks (GANs) with a sensitivity of 88\% and specificity of 99.9\% for pixel-wise localization and a sensitivity of 98\% and a specificity of 100\% for frame-wise detection, which fits the requirements for automatic angiectasia detection in real clinical settings.},
	author = {Pogorelov, Konstantin and Ostroukhova, Olga and Petlund, Andreas and Halvorsen, P{\r a}l and Espeland, H{\r a}vard and Kupka, Tomas and de Lange, Thomas and Griwodz, Carsten and Riegler, Michael}
}
@inproceedings {runeMedico2018,
	title = {Automatic Hyperparameter Optimization in Keras for the MediaEval 2018 Medico Multimedia Task},
	journal = {Working Notes Proceedings of the MediaEval 2018 Workshop},
	year = {2018},
	publisher = {CEUR Workshop Proceedings (CEUR-WS.org)},
	abstract = {This paper details the approach to the MediaEval 2018 Medico Multimedia Task made by the Rune team. The decided upon approach uses a work-in-progress hyperparameter optimization system called Saga. Saga is a system for creating the best hyperparameter finding in Keras, a popular machine learning framework, using Bayesian optimization and transfer learning. In addition to optimizing the Keras classifier configuration, we try manipulating the dataset by adding extra images in a class lacking in images and splitting a commonly misclassified class into two classes.},
	keywords = {automatic hyperparameter optimization, Bayesian optimization, CNN, convolutional neural networks, dataset manipulation, gpyopt, hyperparameter optimization, keras, saga, tensorflow, Transfer Learning},
	author = {Borgli, Rune and Halvorsen, P{\r a}l and Riegler, Michael and H{\r a}kon Kvale {Stensland}}
}
@inproceedings {25904,
	title = {Autonomic Adaptation of Multimedia Content Adhering to Application Mobility},
	journal = {Distributed Applications and Interoperable Systems (DAIS 2018)},
	volume = {10853},
	year = {2018},
	month = {06/2018},
	pages = {153-168},
	publisher = {Springer, Cham},
	edition = {Lecture Notes in Computer Science},
	abstract = {Today,manyusersofmultimediaapplicationsaresurrounded by a changing set of multimedia-capable devices. However, users can move their running multimedia applications only to a pre-defined set of devices. Application mobility is the paradigm where users can move their running applications (or parts of) to heterogeneous devices in a seamless manner. In order to continue multimedia processing under the implied context changes in application mobility, applications need to adapt the presentation of multimedia content and their internal configuration. We propose the system DAMPAT that implements an adaptation control loop to adapt multimedia pipelines. Exponential combinatorial growth of possible pipeline configurations is controlled by architectural constraints specified as high-level goals by application developers. Our evaluation shows that the pipeline only needs to be interrupted a few tens of milliseconds to perform the reconfiguration. Thus, production or consumption of multimedia content can continue across heterogeneous devices and user context changes in a seamless manner.},
	isbn = {978-3-319-93766-3},
	doi = {https://doi.org/10.1007/978-3-319-93767-0_11},
	author = {Francisco Javier {Velazquez-Garcia} and Halvorsen, P{\r a}l and H{\r a}kon Kvale {Stensland} and Eliassen, Frank},
	editor = {Bonomi, S. and Rivi{\`e}re, E.}
}
@inbook {25869,
	title = {Camera Synchronization for Panoramic Videos},
	booktitle = {MediaSync},
	year = {2018},
	month = {03/2018},
	pages = {565-592},
	publisher = {Springer},
	organization = {Springer},
	doi = {10.1007/978-3-319-65840-7_20},
	url = {https://doi.org/10.1007/978-3-319-65840-7_20},
	author = {Vamsidhar Reddy {Gaddam} and Langseth, Ragnar and H{\r a}kon Kvale {Stensland} and Griwodz, Carsten and Riegler, Michael and Kupka, Tomas and Espeland, H{\r a}vard and Johansen, Dag and Johansen, H{\r a}vard and Halvorsen, P{\r a}l},
	editor = {Montagud, Mario and Cesar, Pablo and Boronat, Fernando and Jansen, Jack}
}
@inproceedings {25950,
	title = {Comprehensible Reasoning and Automated Reporting of Medical Examinations Based on Deep Learning Analysis},
	journal = {Proceedings of the 9th ACM Multimedia Systems Conference},
	year = {2018},
	pages = {490-493},
	publisher = {ACM},
	address = {Amsterdam, Netherlands},
	isbn = {978-1-4503-5192-8},
	doi = {10.1145/3204949.3208113},
	author = {Hicks, Steven and Pogorelov, Konstantin and Lux, Mathias and Jeppsson, Mattis and Kristin Ranheim {Randel} and de Lange, Thomas and Sigrun Losadal {Eskeland} and Halvorsen, P{\r a}l and Riegler, Michael}
}
@inproceedings {25794,
	title = {Deep Learning and Handcrafted Feature Based Approaches for Automatic Detection of Angiectasia},
	journal = {2018 IEEE Conference on Biomedical and Health Informatics (BHI)},
	year = {2018},
	pages = {365-368},
	publisher = {IEEE},
	abstract = {Angiectasia, formerly called angiodysplasia, is one of the most frequent vascular lesions and often the cause of gastrointestinal bleedings. Medical specialists assessing videos or images of examinations reach a detection performance of 16\% for the detection of bleeding to 69\% for the detection of angiectasia. This shows that automatic detection to support medical experts can be useful. In this paper, we present several machine learning-based approaches for angiectasia detection in wireless video capsule endoscopy frames. In summary, the most promising results for pixel-wise localization and framewise detection are obtained by the proposed deep learning method using generative adversarial networks (GANs). Using this approach, we achieve a sensitivity of 88\% and specificity of 99.9\% for pixel-wise localization, and a sensitivity of 98\% and a specificity of 100\% for frame-wise detection. Thus, the results demonstrate the capability of using deep learning for automatic angiectasia detection in real clinical settings.\&nbsp;},
	keywords = {Angiectasia, computer aided diagnosis, deep learning, Machine learning, video capsular endoscopy},
	doi = {10.1109/BHI.2018.8333444},
	author = {Pogorelov, Konstantin and Ostroukhova, Olga and Petlund, Andreas and Halvorsen, P{\r a}l and de Lange, Thomas and Espeland, H{\r a}vard and Kupka, Tomas and Griwodz, Carsten and Riegler, Michael}
}
@inproceedings {25954,
	title = {Deep Learning and Hand-crafted Feature Based Approaches for Polyp Detection in Medical Videos},
	journal = {31st IEEE CBMS International Symposium on Computer-Based Medical Systems},
	year = {2018},
	pages = {381-386},
	publisher = {IEEE},
	address = {Karlstad, Sweden},
	issn = {2372-9198},
	doi = {10.1109/CBMS.2018.00073},
	author = {Pogorelov, Konstantin and Ostroukhova, Olga and Jeppsson, Mattis and Espeland, H{\r a}vard and Griwodz, Carsten and de Lange, Thomas and Johansen, Dag and Riegler, Michael and Halvorsen, P{\r a}l}
}
@inproceedings {26259,
	title = {Deep learning approaches for flood classification and flood aftermath detection},
	journal = {Working Notes Proceedings of the MediaEval 2018 Workshop},
	volume = {2283},
	year = {2018},
	publisher = {CEUR-WS.org},
	address = {Sophia Antipolis, France},
	abstract = {This paper presents the method proposed by team UTAOS for MediaEval 2018 Multimedia Satellite Task: Emergency Response for Flooding Events. In the first challenge, we mainly rely on object and scene level features extracted through multiple deep models pre-trained on the ImageNet and Places datasets. The object and scene-level features are combined using early, late and double fusion techniques achieving an average F1-score of 65.03\%, 60.59\% and 63.58\%, respectively. For the second challenge, we rely on a convolutional neural networks (CNNs) and a transfer learning-based classification approach achieving an average F1-score of 62.30\% and 61.02\% for run 1 and run 2, respectively.},
	author = {Said, Naina and Pogorelov, Konstantin and Ahmad, Kashif and Riegler, Michael and Ahmad, Nasir and Ostroukhova, Olga and Halvorsen, P{\r a}l and Conci, Nicola}
}
@inproceedings {26207,
	title = {Deep Learning Based Disease Detection Using Domain Specific Transfer Learning},
	journal = {MediaEval 2018},
	year = {2018},
	publisher = {MediaEval},
	abstract = {In this paper, we present our approach for the Medico Multimedia\&nbsp;Task as part of the MediaEval 2018 Benchmark. Our method is based on convolutional neural networks (CNNs), where we compare how fine-tuning, in the context of transfer learning, from different source domains (general versus medical domain) affect classification\&nbsp;performance. The preliminary results show that fine-tuning models trained on large and diverse datasets is favorable, even when the model{\textquoteright}s source domain has little to no resemblance to the new target.\&nbsp;},
	keywords = {convolutional neural networks, deep learning, Gastrointestinal Disease Detection},
	author = {Hicks, Steven and Pia H. {Smedsrud} and Halvorsen, P{\r a}l and Riegler, Michael}
}
@inproceedings {25956,
	title = {Dissecting Deep Neural Networks for Better Medical Image Classification and Classification Understanding},
	journal = {31st IEEE CBMS International Symposium on Computer-Based Medical Systems},
	year = {2018},
	publisher = {IEEE},
	address = {Karlstad, Sweden},
	issn = {2372-9198},
	doi = {10.1109/CBMS.2018.00070},
	author = {Hicks, Steven and Riegler, Michael and Pogorelov, Konstantin and de Lange, Thomas and Kristin Ranheim {Randel} and Kim V. {{\r A}nonsen} and Jeppsson, Mattis and Halvorsen, P{\r a}l and Sigrun Losadal {Eskeland}}
}
@inproceedings {25903,
	title = {Dynamic Adaptation of Multimedia Presentations for Videoconferencing in Application Mobility},
	journal = {IEEE International Conference on Multimedia and Expo (ICME)},
	year = {2018},
	month = {07/2018},
	publisher = {IEEE},
	address = {San Diego, CA, USA},
	abstract = {Application mobility is the paradigm where users can move their running applications to heterogeneous devices in a seamless manner. This mobility involves dynamic context changes of hardware, network resources, user environment, and user preferences. In order to continue multimedia processing under these context changes, applications need to adapt not only the collection of media streams, i.e.,\&nbsp;multimedia presentation, but also their internal configuration to work on different hardware. We present the performance analysis to adapt a video-conferencing prototype application in a proposed adaptation control loop to autonomously adapt multimedia pipelines. Results show that the time spent to create an adaptation plan and execute it is in the order of hundreds of milliseconds. The reconfiguration of pipelines, compared to building them from scratch, is approximately\&nbsp;1000\&nbsp;times faster when re-utilizing already instantiated hardware-dependent components. Therefore, we conclude that the adaptation of multimedia pipelines is a feasible approach for multimedia applications that adhere to application mobility.},
	issn = {1945-7871},
	doi = {10.1109/ICME.2018.8486565},
	author = {Francisco Javier {Velazquez-Garcia} and Halvorsen, P{\r a}l and H{\r a}kon Kvale {Stensland} and Eliassen, Frank}
}
@inproceedings {26250,
	title = {Efficient Live and on-Demand Tiled HEVC 360 VR Video Streaming},
	journal = {2018 IEEE International Symposium on Multimedia (ISM)},
	year = {2018},
	month = {12/2018},
	pages = {81-88},
	publisher = {IEEE},
	address = {Taichung, Taiwan},
	abstract = {With 360{\textopenbullet} panorama video technology becoming commonplace, the need for efficient streaming methods for such videos arises. We go beyond the existing on-demand solutions and present a live streaming system which strikes a trade-off between bandwidth usage and the video quality in the user{\textquoteright}s field-of-view. We have created an architecture that combines RTP and DASH to deliver 360{\textopenbullet} VR content to a Huawei set-top-box and a Samsung Galaxy S7. Our system multiplexes a single HEVC hardware decoder to provide faster quality switching than at the traditional GOP boundaries. We demonstrate the performance and illustrate the trade-offs through real-world experiments where we can report comparable bandwidth savings to existing on-demand approaches, but with faster quality switches when the field-of- view changes.\&nbsp;},
	doi = {10.1109/ISM.2018.00022},
	author = {Jeppsson, Mattis and Espeland, H{\r a}vard and Kupka, Tomas and Langseth, Ragnar and Petlund, Andreas and Qiaoqiao, Peng and Xue, Chuansong and Pogorelov, Konstantin and Riegler, Michael and Johansen, Dag and Griwodz, Carsten and Halvorsen, P{\r a}l}
}
@inproceedings {25990,
	title = {Flexible Device Sharing in PCIe Clusters using Device Lending},
	journal = {International Conference on Parallel Processing Companion (ICPP{\textquoteright}18 Comp)},
	year = {2018},
	month = {08/2018},
	publisher = {ACM},
	abstract = {Processing workloads may have very high IO demands, exceeding the capabilities provided by resource virtualization and requiring direct access to the physical hardware. For computers that are interconnected in PCI Express (PCIe) networks, we have previously proposed Device Lending as a solution for assigning devices to remote hosts. In this paper, we explain how we have extended our\&nbsp;implementation with support for the Linux Kernel-based Virtual Machine (KVM) hypervisor. Using our extended Device Lending, it becomes possible to dynamically {\textquotedblleft}pass through{\textquotedblright} physical remote devices\&nbsp;to VM guests while still retaining the flexibility of virtualization, something that previously required extensive facilitation in both hypervisor and device drivers in the form of paravirtualization.We have also improved our original implementation with sup- port for interoperability between remote devices. We show that it is possible to use multiple devices residing in different hosts, while still\&nbsp;achieving the same bandwidth and latency as native PCIe, and without requiring any additional support in device drivers.},
	isbn = {978-1-4503-6523-9/18/08},
	doi = {https://doi.org/10.1145/3229710.3229759},
	author = {Markussen, Jonas and Lars Bj{\o}rlykke {Kristiansen} and H{\r a}kon Kvale {Stensland} and Seifert, Friedrich and Griwodz, Carsten and Halvorsen, P{\r a}l}
}
@inproceedings {26274,
	title = {GameStory Task at MediaEval 2018},
	journal = {Proceeding of the MediaEval Benchmarking Initiative for Multimedia Evaluation},
	year = {2018},
	month = {10/2018},
	publisher = {CEUR Workshop Proceedings},
	abstract = {That video games have reached the masses is well known. Moreover, game streaming and watching other people play video games is a phenomenon that has outgrown its small beginnings. Game video streams, be it live or recorded, are viewed by millions. E-sports is the result of organized leagues and tournaments in which players can compete in controlled environments and viewers can experience the matches, discuss and criticize, just like in physical sports. In the GameStory task, taking place the first time in 2018, we approach the game streaming and e-sports phenomena from a multimedia research side. We focus on the task of summarizing matches using a specific relevant game,\&nbsp;Counter-Strike: Global Offensive, as a case study. With the help of ZNIPE.tv, we provide a data set of high quality data and meta data from competitive tournaments and aim to foster research in the area of e-sports and game streaming.},
	author = {Lux, Mathias and Riegler, Michael and Dang-Nguyen, Duc-Tien and Larson, Marcus and Potthast, Martin and Halvorsen, P{\r a}l}
}
@inproceedings {26251,
	title = {The Importance of Medical Multimedia},
	journal = {2018 ACM Multimedia Conference (MM {\textquoteright}18)},
	year = {2018},
	month = {10/2018},
	pages = {2106-2108},
	publisher = {ACM Press},
	address = {New York, NY, USA},
	abstract = {Multimedia research is becoming more and more important for the medical domain, where an increasing number of videos and images are integrated in the daily routine of surgical and diagnostic work. While the collection of medical multimedia data is not an issue, appropriate tools for efficient use of this data are missing. This includes management and inspection of the data, visual analytics, as well as learning relevant semantics and using recognition results for optimizing surgical and diagnostic processes. The characteristics and requirements in this interesting but challenging field are different than the ones in classic multimedia domains. Therefore, this tutorial gives a general introduction to the field, provides a broad overview of specific requirements and challenges, discusses existing work and open challenges, and elaborates in detail how machine learning approaches can help in multimedia-related fields to improve the performance of surgeons/clinicians.\&nbsp;},
	isbn = {9781450356657},
	doi = {10.1145/3240508.3241475},
	url = {http://dl.acm.org/citation.cfm?doid=3240508http://dl.acm.org/citation.cfm?doid=3240508.3241475http://dl.acm.org/ft_gateway.cfm?id=3241475\&ftid=2009687\&dwn=1},
	author = {Riegler, Michael and Halvorsen, P{\r a}l and M{\"u}nzer, Bernd and Schoeffmann, Klaus}
}
@inproceedings {26256,
	title = {Medico Multimedia Task at MediaEval 2018},
	journal = {Working Notes Proceedings of the MediaEval 2018 Workshop},
	year = {2018},
	publisher = {CEUR Workshop Proceedings},
	abstract = {The Medico: Multimedia for Medicine Task, running for the second time as part of MediaEval 2018, focuses on detecting abnormalities, diseases, anatomical landmarks and other findings in images captured by medical devices in the gastrointestinal tract. The task is described, including the use case and its challenges, the dataset with ground truth, the required participant runs and the evaluation metrics.},
	author = {Pogorelov, Konstantin and Riegler, Michael and Halvorsen, P{\r a}l and Hicks, Steven and Kristin Ranheim {Randel} and Dang-Nguyen, Duc-Tien and Lux, Mathias and Ostroukhova, Olga and de Lange, Thomas}
}
@inproceedings {26205,
	title = {The Medico-Task 2018: Disease Detection in the Gastrointestinal Tract using Global Features and Deep Learning},
	journal = {MediaEval 2018},
	year = {2018},
	month = {10/2018},
	publisher = {MediaEval},
	address = {Nice, France},
	abstract = {In this paper, we present our approach for the 2018 Medico Task classifying diseases in the gastrointestinal tract. We have proposed a system based on global features and deep neural networks. The best approach combines two neural networks and the reproducible experimental results signify the efficiency of the proposed model with an accuracy rate of 95.80\%, a precision of 95.87\%, and an F1-score of 95.80\%.},
	keywords = {CNN, deep learning, Gastrointestinal Disease Detection, Global Features, Medico-Task 2018, Transfer Learning},
	author = {Thambawita, Vajira and Jha, Debesh and Riegler, Michael and Halvorsen, P{\r a}l and Hugo Lewi {Hammer} and H{\r a}vard D. {Johansen} and Johansen, Dag}
}
@article {26245,
	title = {Methodology to develop machine learning algorithms to improve performance in gastrointestinal endoscopy},
	journal = {World Journal of Gastroenterology},
	volume = {45},
	year = {2018},
	month = {12/2018},
	pages = {5057-5062},
	publisher = {Baishideng Publishing Group Inc},
	abstract = {Assisted diagnosis using artificial intelligence has been a holy grail in medical research for many years, and recent developments in computer hardware have enabled the narrower area of machine learning to equip clinicians with potentially useful tools for computer assisted diagnosis (CAD) systems. However, training and assessing a computer{\textquoteright}s ability to diagnose like a human are complex tasks, and successful outcomes depend on various factors. We have focused our work on gastrointestinal (GI) endoscopy because it is a cornerstone for diagnosis and treatment of diseases of the GI tract. About 2.8 million luminal GI (esophageal, stomach, colorectal) cancers are detected globally every year, and although substantial technical improvements in endoscopes have been made over the last 10-15 years, a major limitation of endoscopic examinations remains operator variation. This translates into a substantial inter-observer variation in the detection and assessment of mucosal lesions, causing among other things an average polyp miss-rate of 20\% in the colon and thus the subsequent development of a number of post-colonoscopy colorectal cancers. CAD systems might eliminate this variation and lead to more accurate diagnoses. In this editorial, we point out some of the current challenges in the development of efficient computer-based digital assistants. We give examples of proposed tools using various techniques, identify current challenges, and give suggestions for the development and assessment of future CAD systems.\&nbsp;},
	doi = {10.3748/wjg.v24.i45.5057},
	url = {https://www.wjgnet.com/1007-9327/abstract/v24/i45/5057.htm},
	author = {de Lange, Thomas and Halvorsen, P{\r a}l and Riegler, Michael}
}
@inproceedings {25953,
	title = {Mimir: An Automatic Reporting and Reasoning System for Deep Learning based Analysis in the Medical Domain},
	journal = {Proceedings of the 9th ACM Multimedia Systems Conference},
	year = {2018},
	pages = {369-374},
	publisher = {ACM},
	address = {Amsterdam, Netherlands},
	isbn = {978-1-4503-5192-8},
	doi = {10.1145/3204949.3208129},
	author = {Hicks, Steven and Lux, Mathias and de Lange, Thomas and Kristin Ranheim {Randel} and Jeppsson, Mattis and Pogorelov, Konstantin and Halvorsen, P{\r a}l and Riegler, Michael}
}
@article {25870,
	title = {Multimodal analysis of user behavior and browsed content under different image search intents},
	journal = {International Journal of Multimedia Information Retrieval},
	volume = {7},
	year = {2018},
	month = {Jan-03-2018},
	pages = {29 - 41},
	publisher = { Springer},
	abstract = {The motivation or intent of a search for content may vary between users and use-cases. Knowledge and understanding of these underlying objectives may therefore be important in order to return appropriate search results, and studies of user search intent are emerging in information retrieval to understand\&nbsp;why\&nbsp;a user is searching for a particular type of content. In the context of image search, our work targets automatic recognition of users{\textquoteright} intent in an early stage of a search session. We have designed seven different search scenarios under the intent conditions of\&nbsp;finding\&nbsp;items,\&nbsp;re-finding\&nbsp;items and\&nbsp;entertainment. Moreover, we have collected facial expressions, physiological responses, eye gaze and implicit user interactions from 51 participants who performed seven different search tasks on a custom-built image retrieval platform, and we have analyzed the users{\textquoteright} spontaneous and explicit reactions under different intent conditions. Finally, we trained different machine learning models to predict users{\textquoteright} search intent from the visual content of the visited images, the user interactions and the spontaneous responses. Our experimental results show that after fusing the visual and user interaction features, our system achieved the F-1 score of 0.722 for classifying three classes in a user-independent cross-validation. Eye gaze and implicit user interactions, including mouse movements and keystrokes are the most informative features for intent recognition. In summary, the most promising results are obtained by modalities that can be captured unobtrusively and online, and the results therefore demonstrate the potential of including intent-based methods in multimedia retrieval platforms.},
	issn = {2192-6611},
	doi = {10.1007/s13735-018-0150-6},
	url = {http://link.springer.com/10.1007/s13735-018-0150-6http://link.springer.com/content/pdf/10.1007/s13735-018-0150-6.pdfhttp://link.springer.com/article/10.1007/s13735-018-0150-6/fulltext.htmlhttp://link.springer.com/content/pdf/10.1007/s13735-018-0150-6.pdf},
	author = {Soleymani, Mohammad and Riegler, Michael and Halvorsen, P{\r a}l}
}
@inproceedings {25951,
	title = {OpenSea - Open Search Based Classification Tool},
	journal = {Proceedings of the 9th ACM Multimedia Systems Conference},
	year = {2018},
	pages = {363-368},
	publisher = {ACM},
	address = {Amsterdam, Netherlands},
	isbn = {978-1-4503-5192-8},
	doi = {10.1145/3204949.3208128},
	author = {Pogorelov, Konstantin and Albisser, Zeno and Ostroukhova, Olga and Lux, Mathias and Johansen, Dag and Halvorsen, P{\r a}l and Riegler, Michael}
}
@inproceedings {26247,
	title = {Popsift: a faithful SIFT implementation for real-time applications},
	journal = {Proceedings of the 9th ACM Multimedia Systems Conference},
	year = {2018},
	month = {06/2018},
	pages = {415-420},
	publisher = {ACM Press},
	address = {New York, NY, USA},
	isbn = {9781450351928},
	doi = {10.1145/320494910.1145/3204949.3208136},
	url = {http://dl.acm.org/citation.cfm?doid=3204949http://dl.acm.org/citation.cfm?doid=3204949.3208136http://dl.acm.org/ft_gateway.cfm?id=3208136\&ftid=1982183\&dwn=1},
	author = {Griwodz, Carsten and Calvet, Lilian and Halvorsen, P{\r a}l}
}
@article {26246,
	title = {Quantified Soccer Using Positional Data: A Case Study},
	journal = {Frontiers in Physiology},
	volume = {9},
	year = {2018},
	month = {Jun-07-2018},
	pages = {866},
	publisher = {Frontiers},
	abstract = {Performance development in international soccer is undergoing a silent revolution fueled by the rapidly increasing availability of athlete quantification data and advanced analytics. Objective performance data from teams and individual players are increasingly being collected automatically during practices and more recently also in matches after FIFA{\textquoteright}s 2015 approval of wearables in electronic performance and tracking systems. Some clubs have even started collecting data from players outside of the sport arenas. Further algorithmic analysis of these data might provide vital insights for individual training personalization and injury prevention, and also provide a foundation for evidence-based decisions for team performance improvements. This paper presents our experiences from using a detailed radio-based wearable positioning data system in an elite soccer club. We demonstrate how such a system can detect and find anomalies, trends, and insights vital for individual athletic and soccer team performance development. As an example, during a normal microcycle (6 days) full backs only covered 26\% of the sprint distance they covered in the next match. This indicates that practitioners must carefully consider to proximity size and physical work pattern in microcycles to better resemble match performance. We also compare and discuss the accuracy between radio waves and GPS in sampling tracking data. Finally, we present how we are extending the radio-based positional system with a novel soccer analytics annotation system, and a real-time video processing system using a video camera array. This provides a novel toolkit for modern forward-looking soccer coaches that we hope to integrate in future studies.\&nbsp;},
	doi = {10.3389/fphys.2018.00866},
	url = {https://www.frontiersin.org/article/10.3389/fphys.2018.00866/fullhttps://www.frontiersin.org/article/10.3389/fphys.2018.00866/full},
	author = {Svein A. {Pettersen} and H{\r a}vard D. {Johansen} and Ivan A. M. {Baptista} and Halvorsen, P{\r a}l and Johansen, Dag}
}
@article {26257,
	title = {Social Media and Satellites. Disaster event detection, linking and summarization},
	journal = {Multimedia Tools and Applications},
	volume = {78},
	year = {2018},
	pages = {2837{\textendash}2875},
	publisher = {Springer},
	address = {US},
	abstract = {Being able to automatically link social media and satellite imagery holds large opportunities for research, with a potentially considerable impact on society. The possibility of integrating different information sources opens in fact to new scenarios where the wide coverage of satellite imaging can be used as a collector of the fine-grained details provided by the social media. Remote-sensed data and social media data can well complement each other, integrating the wide perspective provided by the satellite view with the information collected locally, being it textual, audio, or visual. Among the possible applications, natural disasters are certainly one of the most interesting scenarios, where global and local perspectives are needed at the same time.In this paper, we present a system called JORD that is able to autonomously collect social media data (including the text analysis in local languages) about technological and environmental disasters, and link it automatically to remote-sensed data. Moreover, in order to ensure the quality of retrieved information, JORD is equipped with a hierarchical filtering mechanism relying on the temporal information and the content analysis of retrieved multimedia data.To show the capabilities of the system, we present a large number of disaster events detected by the system, and we evaluate both the quality of the provided information about the events and the usefulness of JORD from potential users viewpoint, using crowdsourcing.},
	keywords = {Event Detection, Information retrieval, Natural Disaster, Social Media},
	doi = {10.1007/s11042-018-5982-9},
	author = {Ahmad, Kashif and Pogorelov, Konstantin and Riegler, Michael and Conci, Nicola and Halvorsen, P{\r a}l}
}
@inproceedings {26275,
	title = {Team ORG @ GameStory Task 2018},
	journal = {Proceeding of the MediaEval Benchmarking Initiative for Multimedia Evaluation},
	year = {2018},
	month = {10/2018},
	publisher = {MediaEval},
	abstract = {This paper describes the approach of the organizers{\textquoteright} team for a submission to the GameStory task at MediaEval 2018. Goal of the task is to provide a summary of a \&nbsp;match of Counter Strike: Global Offensive\&nbsp;(CS:GO), a popular e-sports game, that boils down a long game to it{\textquoteright}s most important events and delivers a story on the progress of the match. Our approach was to provide match statistics and overlay them with events and highlights of the game. We focused on ends of critical rounds, i.e. the rounds where one team took the lead over the other one, and kill streaks, where one player eliminated a substantial number of other players in short time.\&nbsp;},
	author = {Lux, Mathias and Riegler, Michael and Dang-Nguyen, Duc-Tien and Larson, Marcus and Potthast, Martin and Halvorsen, P{\r a}l}
}
@inproceedings {26249,
	title = {Tradeoffs using Binary and Multiclass Neural Network Classification for Medical Multidisease Detection},
	journal = {2018 IEEE International Symposium on Multimedia (ISM)},
	year = {2018},
	month = {12/2018},
	pages = {1-8},
	publisher = {IEEE},
	abstract = {The interest in neural networks has increased sig- nificantly, and the application of this type of machine learning is vast, ranging from natural image classification to medical image segmentation. However, many users of neural networks tend to use them as a black box tool. They do not access all of the possible variations, nor take into account the respective classification accuracies and costs. In our work, we focus on multiclass image classification, and in this research, we shed light on the trade-offs between systems using a single multiclass classification and multiple binary classifiers, respectively. We have tested the these classifiers on several modern neural network architectures, including DenseNet, Inception v3, Inception ResNet v2, Xception, NASNet and MobileNet. We have compared several aspects of the performance of these architectures during training and testing using both classification styles. We have compared classification speed and several classification accuracy metrics. Here, we present the results from experiments on a total of 99 networks: 11 multiclass and 88 individual binary networks, for an 8-class classification of medical images. In short, using multiple binary classification networks resulted in a 7\% increase in the average F1 score, a 1\% increase in average accuracy, a 1\% increase in precision, and a 4\% increase in average recall. However, on average, such a multi-network style performed the classification 7.6 times slower compared to a single network multiclass implementation. These collective findings show that both approaches can be applied to modern neural network structures. Several binary networks will often give increased classification accuracy, but at the cost of classification speed and resource consumption.\&nbsp;},
	doi = {10.1109/ISM.2018.00009},
	author = {Tor Jan Derek {Berstad} and Riegler, Michael and Espeland, H{\r a}vard and de Lange, Thomas and Pia H. {Smedsrud} and Pogorelov, Konstantin and H{\r a}kon Kvale {Stensland} and Halvorsen, P{\r a}l}
}
@inproceedings {26258,
	title = {Transfer learning with prioritized classification and training dataset equalization for medical objects detection},
	journal = {Working Notes Proceedings of the MediaEval 2018 Workshop},
	year = {2018},
	publisher = {CEUR Workshop Proceedings},
	abstract = {This paper presents the method proposed by the organizer team (SIMULA) for MediaEval 2018 Multimedia for Medicine: the Medico Task. We utilized the recent transfer-learning-based image classification methodology and focused on how easy it is to implement multi-class image classifiers in general and how to improve the classification performance without deep neural network model redesign. The goal for this was both to provide a baseline for the Medico task and to show the\&nbsp; performance of out-of-the-box classifiers for the medical use-case scenario.},
	author = {Ostroukhova, Olga and Pogorelov, Konstantin and Riegler, Michael and Dang-Nguyen, Duc-Tien and Halvorsen, P{\r a}l}
}
@inproceedings {26254,
	title = {Using preprocessing as a tool in medical image detection},
	journal = {MediaEval 2018},
	year = {2018},
	month = {10/2018},
	publisher = {MediaEval},
	address = {Nice, France},
	abstract = {In this paper, we describe our approach to gastrointestinal disease classification for the medico task at MediaEval 2018. We propose multiple ways to inpaint problematic areas in the test and training set to help with classification. We discuss the effect that preprocessing does to the input data with respect to removing regions with sparse information. We also discuss how preprocessing affects the training and evaluation of a dataset that is limited in size. We will also compare the different inpainting methods with transfer learning using a convolutional neural network.},
	keywords = {classification, Image processing, Machine Leanring},
	author = {Kirker{\o}d, Mathias and Thambawita, Vajira and Riegler, Michael and Halvorsen, P{\r a}l}
}
@inproceedings {25268,
	title = {ClusterTag: Interactive Visualization, Clustering and Tagging Tool for Big Image Collections},
	journal = {ACM International Conference on Multimedia Retrieval},
	year = {2017},
	month = {06/2017},
	publisher = {ACM},
	address = {Bucharest},
	author = {Pogorelov, Konstantin and Riegler, Michael and Halvorsen, P{\r a}l and Griwodz, Carsten}
}
@inproceedings {25629,
	title = {CNN and GAN Based Satellite and Social Media Data Fusion for Disaster Detection},
	journal = {MediaEval Benchmark 2017},
	year = {2017},
	month = {09/2017},
	publisher = {CEUR-WS.org},
	address = {Dublin, Ireland},
	author = {Ahmad, Kashif and Pogorelov, Konstantin and Riegler, Michael and Conci, Nicola and Halvorsen, P{\r a}l},
	editor = {Ahmad, Kashif}
}
@inproceedings {25628,
	title = {A comparison of deep learning with global features for gastrointestinal disease detection},
	journal = {MediaEval Benchmark 2017},
	year = {2017},
	month = {09/2017},
	publisher = {CEUR-WS.org},
	address = {Dublin, Ireland},
	author = {Pogorelov, Konstantin and Riegler, Michael and Halvorsen, P{\r a}l and Griwodz, Carsten and de Lange, Thomas and Kristin Ranheim {Randel} and Sigrun Losada {Eskeland} and Dang-Nguyen, Duc-Tien and Olga, Ostroukhova and Lux, Mathias and Spampinato, Concetto},
	editor = {Riegler, Michael}
}
@article {25462,
	title = {Efficient disease detection in gastrointestinal videos {\textendash} global features versus neural networks},
	journal = {Multimedia Tools and Applications},
	volume = {76},
	year = {2017},
	month = {11/2017},
	pages = {22493{\textendash}22525},
	publisher = {ACM/Springer},
	abstract = {Analysis of medical videos from the human gastrointestinal (GI) tract for detection and localization of abnormalities like lesions and diseases requires both high precision and recall. Additionally, it is important to support efficient, real-time processing for live feedback during (i) standard colonoscopies and (ii) scalability for massive population-based screening, which we conjecture can be done using a wireless video capsule endoscope (camera-pill). Existing related work in this field does neither provide the necessary combination of accuracy and performance for detecting multiple classes of abnormalities simultaneously nor for particular disease localization tasks. In this paper, a complete end-to-end multimedia system is presented where the aim is to tackle automatic analysis of GI tract videos. The system includes an entire pipeline ranging from data collection, processing and analysis, to visualization. The system combines deep learning neural networks, information retrieval, and analysis of global and local image features in order to implement multi-class classification, detection and localization. Furthermore, it is built in a modular way, so that it can be easily extended to deal with other types of abnormalities. Simultaneously, the system is developed for efficient processing in order to provide real-time feedback to the doctors and for scalability reasons when potentially applied for massive population-based algorithmic screenings in the future. Initial experiments show that our system has multiclass detection accuracy and polyp localization precision at least as good as state-of-the-art systems, and provides additional novelty in terms of real-time performance, low resource consumption and ability to extend with support for new classes of diseases.},
	keywords = {Algorithmic screening, Automatic disease detection, Deep learning neural networks, Global and local image features, Information retrieval, Medical, performance evaluation},
	issn = {1380-7501},
	doi = {10.1007/s11042-017-4989-y},
	url = {https://link.springer.com/article/10.1007\%2Fs11042-017-4989-y},
	author = {Pogorelov, Konstantin and Riegler, Michael and Sigrun Losada {Eskeland} and de Lange, Thomas and Johansen, Dag and Griwodz, Carsten and Peter Thelin {Schmidt} and Halvorsen, P{\r a}l}
}
@inproceedings {25338,
	title = {EIR: changing the scene of automatic detection software for gastrointestinal endoscopy},
	journal = {World Congress of GI Endoscopy},
	year = {2017},
	month = {02/2017},
	publisher = {World Endoscopic Organisation},
	address = {Hyderabad, India},
	author = {Sigrun L. {Eskeland} and Aabakken, Lars and Riegler, Michael and Pogorelov, Konstantin and Peter Thelin {Schmidt} and Johansen, Dag and Halvorsen, P{\r a}l},
	editor = {de Lange, Thomas}
}
@inproceedings {25335,
	title = {Finding equilibrium for gym ownership distribution based on game dynamics in Pok{\'e}mon GO game},
	journal = {ACM International Workshop on Massively Multiuser Virtual Environments},
	year = {2017},
	month = {07/2017},
	pages = {1-6},
	publisher = {ACM},
	address = {Taiwan},
	isbn = {978-1-4503-5006-8},
	doi = {10.1145/3083207.3083208},
	author = {Ahmed, Iffat and Riegler, Michael and Petlund, Andreas and Griwodz, Carsten and Halvorsen, P{\r a}l}
}
@article {25265,
	title = {From Annotation to Computer-Aided Diagnosis: Detailed Evaluation of a Medical Multimedia System},
	journal = {ACM Transactions on Multimedia Computing, Communications, and Applications},
	volume = {13},
	year = {2017},
	publisher = {ACM},
	author = {Riegler, Michael and Pogorelov, Konstantin and Sigrun L. {Eskeland} and Peter Thelin {Schmidt} and Albisser, Zeno and Johansen, Dag and Griwodz, Carsten and Halvorsen, P{\r a}l and de Lange, Thomas}
}
@inproceedings {25433,
	title = {A Holistic Multimedia System for Gastrointestinal Tract Disease Detection},
	journal = {8th annual ACM conference on Multimedia Systems (MMSys)},
	year = {2017},
	month = {06/2017},
	pages = {112-123},
	publisher = {ACM},
	abstract = {Analysis of medical videos for detection of abnormalities and diseases requires both high precision and recall, but also real-time processing for live feedback and scalability for massive screening of entire populations. Existing work on this field does not provide the necessary combination of retrieval accuracy and performance.\&nbsp;In this paper, a multimedia system is presented where the aim is to tackle automatic analysis of videos from the human gastrointestinal (GI) tract. The system includes the whole pipeline from data collection, processing and analysis, to visualization. The system combines filters using machine learning, image recognition and extraction of global and local image features. Furthermore, it is built in a modular way so that it can easily be extended. At the same time, it is developed for efficient processing in order to provide real-time feedback to the doctors. Our experimental evaluation proves that our system has detection and localisation accuracy at least as good as existing systems for polyp detection, it is capable of detecting a wider range of diseases, it can analyze video in real-time, and it has a low resource consumption for scalability.},
	isbn = {978-1-4503-5002-0},
	doi = {10.1145/3083187.3083189},
	url = {http://dl.acm.org/citation.cfm?id=3083189},
	author = {Pogorelov, Konstantin and Sigrun Losadal {Eskeland} and de Lange, Thomas and Griwodz, Carsten and Kristin Ranheim {Randel} and H{\r a}kon Kvale {Stensland} and Dang-Nguyen, Duc-Tien and Spampinato, Concetto and Johansen, Dag and Riegler, Michael and Halvorsen, P{\r a}l},
	editor = {Cesar, Pablo and Hsu, Cheng-hsin}
}
@inproceedings {25812,
	title = {JORD: A System for Collecting Information and Monitoring Natural Disasters by Linking Social Media with Satellite Imagery},
	journal = {Proceedings of the 15th International Workshop on Content-Based Multimedia Indexing  - CBMI {\textquoteright}17},
	year = {2017},
	pages = {12:1--12:6},
	publisher = {ACM Press},
	address = {New York, USA},
	abstract = {Gathering information, and continuously monitoring the affected areas after a natural disaster can be crucial to assess the damage, and speed up the recovery process. Satellite imagery is being considered as one of the most productive sources to monitor the after effects of a natural disaster; however, it also comes with a lot of challenges and limitations, due to slow update. It would be beneficiary to link remote sensed data with social media for the damage assessment, and obtaining detailed information about a disaster. The additional information, which are obtainable by social media, can enrich remote-sensed data, and overcome its limitations. To tackle this, we present a system called JORD that is able to autonomously collect social media data about natural disasters, and link it automatically to remote-sensed data. In addition, we demonstrate that queries in local languages that are relevant to the exact position of natural disasters retrieve more accurate information about a disaster event. We also provide content based analysis along with temporal and geo-location based filtering to provide more accurate information to the users. To show the capabilities of the system, we demonstrate that a large number of disaster events can be detected by the system. In addition, we use crowdsourcing to demonstrate the quality of the provided information about the disasters, and usefulness of JORD from potential users point of view.},
	isbn = {9781450353335},
	doi = {10.1145/3095713.3095726},
	url = {http://dl.acm.org/citation.cfm?doid=3095713},
	author = {Ahmad, Kashif and Riegler, Michael and Pogorelov, Konstantin and Halvorsen, P{\r a}l and De Natale, Francesco}
}
@inproceedings {25269,
	title = {The JORD System - Linking sky and social multimedia data to Natural and Technological Disasters},
	journal = {ACM International Conference on Multimedia Retrieval},
	year = {2017},
	month = {06/2017},
	publisher = {ACM},
	address = {Bucharest},
	isbn = {978-1-4503-4701-3},
	doi = {10.1145/3078971.3079013},
	author = {Ahmad, Kashif and Riegler, Michael and Riaz, Ans and Conci, Nicola and Dang-Nguyen, Duc-Tien and Halvorsen, P{\r a}l},
	editor = {Ionescu, Bogdan and Sebe, Nicu}
}
@inproceedings {25332,
	title = {Kvasir: A Multi-Class Image-Dataset for Computer Aided Gastrointestinal Disease Detection},
	journal = {ACM Multimedia Systems},
	year = {2017},
	month = {07/2017},
	publisher = {ACM},
	address = {Taiwan},
	author = {Pogorelov, Konstantin and Ranheim, Kristin and Griwodz, Carsten and de Lange, Thomas and Sigrun L. {Eskeland} and Johansen, Dag and Peter Thelin {Schmidt} and Spampinato, Concetto and Dang-Nguyen, Duc-Tien and Lux, Mathias and Riegler, Michael and Halvorsen, P{\r a}l}
}
@inproceedings {25267,
	title = {LireSolr - A Visual Information Retrieval Server},
	journal = {ACM International Conference on Multimedia Retrieval},
	year = {2017},
	month = {06/2017},
	publisher = {ACM},
	address = {Bucharest},
	isbn = {978-1-4503-4701-3},
	doi = {10.1145/3078971.3079014},
	author = {Lux, Mathias and Riegler, Michael and Halvorsen, P{\r a}l and MacStravic, Glenn},
	editor = {Ionescu, Bogdan and Sebe, Nicu}
}
@inproceedings {25432,
	title = {Load Balancing of Multimedia Workloads for Energy Efficiency on the Tegra K1 Multicore Architecture},
	journal = {8th annual ACM conference on Multimedia Systems (MMSys)},
	year = {2017},
	month = {06/2017},
	pages = {124-135},
	publisher = {ACM},
	abstract = {Energy efficiency is a timely topic for modern mobile computing. Reducing the\&nbsp;energy consumption of devices not only increases their battery lifetime, but\&nbsp;also reduces the risk of hardware failure. Many researchers strive tounderstand the relationship between software activity and hardware power usage.\&nbsp;A recurring strategy for saving power is to reduce operating frequencies. It is\&nbsp;widely acknowledged that standard frequency scaling algorithms generally\&nbsp;overreact to changes in hardware utilisation. More recent and original efforts\&nbsp;attempt to balance software workloads on heterogeneous multicore architectures,\&nbsp;such as the Tegra K1, which includes a quad-core CPU and a CUDA-capable GPU.\&nbsp;However, it is not known whether it is possible to utilise these processor\&nbsp;elements in parallel to save energy. Research into these types of systems are\&nbsp;unfortunately often evaluated with the Performance Per Watt (PPW) metric, which\&nbsp;is an unaccurate method because it ignores constant power usage from idle\&nbsp;components. We show that this metric can end up increase energy usage on the\&nbsp;Tegra K1, and give a false impression of how such systems consume energy. \&nbsp;In\&nbsp;reality, we show that it is much harder to save energy by balancing workloads\&nbsp;between the heterogeneous cores of the Tegra K1, where we demonstrate only a 5\%\&nbsp;energy saving by offloading 10\% DCT workload from the GPU to the CPU.\&nbsp;Significantly more energy can be saved (up to 50\%) using the appropriate\&nbsp;processor for different workloads.\&nbsp;},
	isbn = {978-1-4503-5002-0},
	doi = {10.1145/3083187.3083195},
	url = {http://dl.acm.org/citation.cfm?doid=3083187.3083195},
	author = {Kristoffer Robin {Stokke} and H{\r a}kon Kvale {Stensland} and Griwodz, Carsten and Halvorsen, P{\r a}l},
	editor = {Cesar, Pablo and Hsu, Cheng-hsin}
}
@inproceedings {26178,
	title = {Medical Multimedia Information Systems (MMIS)},
	journal = {the 2017 ACMProceedings of the 2017 ACM on Multimedia Conference  - MM {\textquoteright}17},
	year = {2017},
	publisher = {ACM Press},
	address = {Mountain View, California, USANew York, New York, USA},
	isbn = {9781450349062},
	doi = {10.1145/312326610.1145/3123266.3130142},
	url = {http://dl.acm.org/citation.cfm?doid=3123266http://dl.acm.org/citation.cfm?doid=3123266.3130142http://dl.acm.org/ft_gateway.cfm?id=3130142\&ftid=1915055\&dwn=1},
	author = {Schoeffmann, Klaus and M{\"u}nzer, Bernd and Riegler, Michael and Halvorsen, P{\r a}l},
	editor = {Liu, Qiong and Lienhart, Rainer and Wang, Haohong and Sheng-Wei "Kuan-Ta" {Chen} and Boll, Susanne and Chen, Phoebe and Friedland, Gerald and Li, Jia and Yan, Shuicheng}
}
@inproceedings {25632,
	title = {Medical Multimedia Information Systems (MMIS)},
	journal = {ACM Multimedia},
	year = {2017},
	month = {10/2017},
	publisher = {ACM},
	address = {Mountain View},
	author = {Schoeffmann, Klaus and M{\"u}nzer, Bernd and Riegler, Michael and Halvorsen, P{\r a}l},
	editor = {Schoeffmann, Klaus}
}
@inproceedings {25627,
	title = {Multimedia for medicine: the medico Task at mediaEval 2017},
	journal = {MediaEval Benchmark 2017},
	year = {2017},
	month = {09/2017},
	publisher = {CEUR-WS.org},
	address = {Dublin, Ireland},
	author = {Riegler, Michael and Pogorelov, Konstantin and Halvorsen, P{\r a}l and Griwodz, Carsten and de Lange, Thomas and Kristin Ranheim {Randel} and Sigrun Losada {Eskeland} and Dang-Nguyen, Duc-Tien and Lux, Mathias and Spampinato, Concetto},
	editor = {Riegler, Michael}
}
@inproceedings {25334,
	title = {Multimodal Analysis of Image Search Intent - Intent Recognition in Image Search from User Behavior and Visual Content},
	journal = {ACM International Conference on Multimedia Retrieval},
	year = {2017},
	month = {07/2017},
	publisher = {ACM},
	address = {Bucharest},
	isbn = {978-1-4503-4701-3},
	doi = {10.1145/3078971.3078995},
	author = {Soleymani, Mohammad and Riegler, Michael and Halvorsen, P{\r a}l},
	editor = {Ionescu, Bogdan and Sebe, Nicu}
}
@inproceedings {25333,
	title = {Nerthus: A Bowel Preparation Quality Video Dataset},
	journal = {ACM Multimedia Systems},
	year = {2017},
	publisher = {ACM},
	address = {Taipei},
	author = {Pogorelov, Konstantin and Ranheim, Kristin and de Lange, Thomas and Sigrun L. {Eskeland} and Johansen, Dag and Griwodz, Carsten and Spampinato, Concetto and Taschwer, Mario and Lux, Mathias and Peter Thelin {Schmidt} and Riegler, Michael and Halvorsen, P{\r a}l}
}
@inproceedings {24859,
	title = {ChaLearn Joint Contest on Multimedia Challenges Beyond Visual Analysis: An Overview},
	journal = {International Conference on Pattern Recognition},
	year = {2016},
	month = {12/2016},
	publisher = {IEEE},
	address = {Cancun, Mexico},
	abstract = {This paper provides an overview of the Joint Contest on Multimedia Challenges Beyond Visual Analysis. We organized an academic competition that focused on four problems that require effective processing of multimodal information in order to be solved. Two tracks were devoted to gesture spotting and recognition from RGB-D video, two fundamental problems for human computer interaction. Another track was devoted to a second round of the first impressions challenge of which the goal was to develop methods to recognize personality traits from short video clips. For this second round we adopted a novel collaborative-competitive (i.e., coopetition) setting. The fourth track was dedicated to the problem of video recommendation for improving user experience. The challenge was open for about 45 days, and received outstanding participation: almost 200 participants registered to the contest, and 20 teams sent predictions in the final stage. The main goals of the challenge were fulfilled: the state of the art was advanced considerably in the four tracks, with novel solutions to the proposed problems (mostly relying on deep learning). However, further research is still required. The data of the four tracks will be available to allow researchers to keep making progress in the four tracks.},
	author = {V{\'\i}ctor Ponce {L{\'o}pez} and Wan, Jun and Riegler, Michael and Chen, Baiyu and Clap{\'e}s, Albert and Escalera, Sergio and Guyon, Isabelle and Bar{\'o}, Xavier and Halvorsen, P{\r a}l and M{\"u}ller, Henning}
}
@inproceedings {24472,
	title = {Computer Aided Disease Detection System for Gastrointestinal Examinations},
	journal = {Multimedia Systems Conference 2016},
	year = {2016},
	month = {05/2016},
	publisher = {ACM},
	address = {New York},
	author = {Riegler, Michael and Pogorelov, Konstantin and Markussen, Jonas and Lux, Mathias and H{\r a}kon Kvale {Stensland} and de Lange, Thomas and Griwodz, Carsten and Halvorsen, P{\r a}l and Johansen, Dag and Peter Thelin {Schmidt} and Sigrun L. {Eskeland}}
}
@inproceedings {24480,
	title = {Crowdsourcing as Self Fulfilling Prophecy: Influence of Discarding Workers in Subjective Assessment Tasks},
	journal = {International Workshop on Content-based Multimedia Indexing},
	year = {2016},
	month = {06/2016},
	publisher = {IEEE / ACM},
	author = {Riegler, Michael and Vamsidhar Reddy {Gaddam} and Halvorsen, P{\r a}l and Griwodz, Carsten}
}
@inproceedings {24477,
	title = {Device Lending in PCI Express Networks},
	journal = {Proceedings of the 26th International Workshop on Network and Operating Systems Support for Digital Audio and Video (NOSSDAV)},
	year = {2016},
	month = {05/2016},
	pages = {10:1-10:6},
	publisher = {ACM},
	abstract = {The challenge of scaling IO performance of multimedia systems to demands of their users has attracted much research. A lot of effort has gone into development of distributed systems that add little latency and computing overhead. For machines in PCI Express (PCIe) clusters, we propose Device Lending as a novel solution which works at a system level. Device Lending achieves low latency and extremely low computing overhead without requiring any application-specific distribution mechanisms. For applications, the remote IO resource appears local. In fact, even the drivers of the operating system remain unaware that hardware resources are located in remote machines. By enabling machines in a PCIe cluster to lend a wide variety of hardware, cluster machines can get temporary access to a pool of IO resources. Network cards, FPGAs, SSDs, and even GPUs can easily be shared among computers. Our proposed solution, Device Lending, works transparently without requiring any modifications to drivers, operating systems or software applications.},
	isbn = {978-1-4503-4356-5},
	doi = {10.1145/2910642.2910650},
	author = {Markussen, Jonas and H{\r a}kon Kvale {Stensland} and Riegler, Michael and Kohmann, Hugo and Nordstr{\o}m, Roy and Griwodz, Carsten and Halvorsen, P{\r a}l}
}
@inproceedings {24474,
	title = {Efficient Processing of Videos in a Multi Auditory Environment Using Device Lending of GPUs},
	journal = {The 7th International Conference on Multimedia Systems (MMSys)},
	year = {2016},
	month = {05/2016},
	pages = {36:1-36:4},
	publisher = {ACM},
	isbn = {978-1-4503-4297-1},
	doi = {10.1145/2910017.2910636},
	author = {Pogorelov, Konstantin and Riegler, Michael and Markussen, Jonas and H{\r a}kon Kvale {Stensland} and Halvorsen, P{\r a}l and Griwodz, Carsten and Sigrun L. {Eskeland} and de Lange, Thomas}
}
@inproceedings {24482,
	title = {EIR - Efficient Computer Aided Diagnosis Framework for Gastrointestinal Endoscopies},
	journal = {International Workshop on Content-based Multimedia Indexing},
	year = {2016},
	month = {06/2016},
	publisher = {IEEE / ACM},
	author = {Riegler, Michael and Pogorelov, Konstantin and Halvorsen, P{\r a}l and de Lange, Thomas and Griwodz, Carsten and Johansen, Dag and Peter Thelin {Schmidt} and Sigrun L. {Eskeland}}
}
@inproceedings {24481,
	title = {Explorative Hyperbolic-Tree-Based Clustering Tool for Unsupervised Knowledge Discovery},
	journal = {International Workshop on Content-based Multimedia Indexing},
	year = {2016},
	month = {06/2016},
	publisher = {IEEE / ACM},
	author = {Riegler, Michael and Pogorelov, Konstantin and Lux, Mathias and Halvorsen, P{\r a}l and Griwodz, Carsten and Sigrun L. {Eskeland} and de Lange, Thomas}
}
@inproceedings {24478,
	title = {GPU-accelerated Real-time Gastrointestinal Diseases Detection},
	journal = {CBMS 2016 : The 29th International Symposium on Computer-Based Medical Systems},
	year = {2016},
	month = {07/2016},
	publisher = {IEEE},
	author = {Pogorelov, Konstantin and Riegler, Michael and Halvorsen, P{\r a}l and de Lange, Thomas and Peter Thelin {Schmidt} and Sigrun L. {Eskeland} and Griwodz, Carsten and Johansen, Dag}
}
@inproceedings {24541,
	title = {Heimdallr: a dataset for sport analysis},
	journal = {ACM Multimedia System},
	year = {2016},
	month = {05/2016},
	publisher = {ACM},
	abstract = {In this paper, we present Heimdallr, a dataset that aims to serve two different purposes. The first purpose is action recognition and pose estimation, which requires a dataset of annotated sequences of athlete skeletons. We employed a crowdsourcing platform where people around the world were asked to annotate frames and obtained more than 3000 fully annotated frames for 42 different sequences with a variety of poses and actions. The second purpose is an improved understanding of crowdworkers, and for this purpose, we collected over 10000 written feedbacks from 592 crowdworkers. This is valuable information for crowdsourcing researchers who explore algorithms for worker quality assessment. In addition to the complete dataset, we also provide the code for the application that has been used to collect the data as an open source software.},
	doi = {http://dl.acm.org/citation.cfm?doid=2910017.2910621},
	author = {Riegler, Michael and Dang-Nguyen, Duc-Tien and Winther, B{\r a}rd and Griwodz, Carsten and Pogorelov, Konstantin and Halvorsen, P{\r a}l}
}
@misc {24491,
	title = {A High Precision Power Model for the Tegra K1 CPU, GPU and RAM},
	howpublished = {GPU Technology Conference 2016},
	year = {2016},
	month = {04/2016},
	publisher = {Nvidia},
	abstract = {Power modelling is an important topic in many areas of computing, for example to save energy in texture streaming for gaming[1] or to select efficient H.264 video encoding parameters[2]. However, researchers\&$\#$39; view of how hardware consume power is limited. They typically resort to rate\&shy;based models to describe the energy consumption of hardware, where power usage is correlated directly with hardware access rates (for example instructions or cache misses per second)[3,4,5,6]. This approach ignores many mechanisms that impact the power usage of a system, such as rail voltages, core\&shy; and clock\&shy; gating, frequency scaling and variable cost of instruction execution. Because of this, they can mispredict up to 70 \% on the Tegra K1. We show that by taking all these factors into account with sufficient hardware knowledge, it is possible to bridge the gap between power usage and software execution to build power models which are over 98 \% accurate over all CPU, GPU and memory frequency combinations.},
	url = {http://on-demand.gputechconf.com/gtc/2016/posters/images/1920x1607/GTC_2016_Embedded_EM_01_P6326_WEB_1920x1607.png},
	author = {Kristoffer Robin {Stokke} and H{\r a}kon Kvale {Stensland} and Halvorsen, P{\r a}l}
}
@inproceedings {24490,
	title = {A High-Precision, Hybrid GPU, CPU and RAM Power Model for Generic Multimedia Workloads},
	journal = {7th annual ACM conference on Multimedia Systems (MMSys)},
	year = {2016},
	month = {05/2016},
	pages = {14:1-14:12},
	publisher = {ACM},
	abstract = {Energy efficiency of multimedia processing is a hot topic in modern, mobile computing where the lifetime of battery- powered devices is low. Authors often use power models as tools to evaluate the energy-efficiency of multimedia work- loads and processing schemes. A challenge with these mod- els is that they are built without sufficiently deep hardware knowledge and as a result they have the potential to mis- predict substantially depending on hardware configuration. Typical rate-based power models can for example mispredict up to 70 \% on the Tegra K1 SoC. Inspired by multimedia workloads, we introduce a modelling methodology which can be used to build a generic, high-precision power model for the Tegra K1\&rsquo;s GPU and memory. By considering hardware utilisation, rail voltages, leakage currents and clocks, the model achieves an average accuracy above 99 \% over all op- erating frequencies, and has been rigorously tested on several multimedia workloads. Our method exposes detailed insight into hardware and how it consumes energy. This knowledge is not only useful for researchers to understand how power models should be built, but also helps to understand what developers can do to minimise power usage. For example, experiments show that for a DCT benchmark, 3 \% power can be saved by utilising non-coherent caches and smaller datatypes.},
	isbn = {978-1-4503-4297-1},
	doi = {10.1145/2910017.2910591},
	author = {Kristoffer Robin {Stokke} and H{\r a}kon Kvale {Stensland} and Griwodz, Carsten and Halvorsen, P{\r a}l}
}
@inproceedings {24935,
	title = {High-Precision Power Modelling of the Tegra K1 Variable SMP Processor Architecture},
	journal = {10th IEEE International Symposium on Embedded Multicore/Many-core Systems-on-Chip (MCSoC)},
	year = {2016},
	month = {09/2016},
	pages = {193-200},
	publisher = {IEEE},
	abstract = {Energy efficiency is an important issue for many embedded systems, where limited battery lifetime and power- hungry hardware constrain the usefulness of such devices. Modern Systems-on-Chip (SoCs) such as the Tegra K1 employ advanced power management capabilities such as two CPU clus- ters, clock-gating, power-gating and dynamic frequency tuning to meet application demands. At design or runtime phases, it is challenging for system architects and software developers to understand the effects that these mechanisms have in terms of power and performance in all parts of the system. This is especially because it is impossible to measure directly the power usage of cores, caches, memory and other hardware components. Rate-based power models are often proposed as a solution for this, but unfortunately these can mispredict substantially on the Tegra K1 up to 30 \%. In this paper, we propose a power modelling method for the Tegra K1 CPU which overcomes the limitations of the most common types of models found in literature, but still only requires power measurement of the board. Through extensive empirical validation we demonstrate an accuracy which is close to 100 \%. Through preliminary experiments we show that our methodology is able to capture instruction power of individual system processes and applications and produce detailed power breakdowns of all components in the system.},
	doi = {10.1109/MCSoC.2016.28},
	author = {Kristoffer Robin {Stokke} and H{\r a}kon Kvale {Stensland} and Halvorsen, P{\r a}l and Griwodz, Carsten},
	editor = {Le Beux, S{\'e}bastien}
}
@inproceedings {24922,
	title = {ImageCLEF 2017 LifeLog task},
	journal = {Challenges in Machine Learning: Gaming and Education (CiML - NIPS 2016 workshop)},
	year = {2016},
	month = {11/2016},
	publisher = {NIPS},
	address = {Barcelona, Spain},
	author = {Dang-Nguyen, Duc-Tien and Piras, Luca and Riegler, Michael and Gurrin, Cathal and Boato, Giulia and Halvorsen, P{\r a}l}
}
@inproceedings {24962,
	title = {Immersed gaming in Minecraft},
	journal = {The 7th ACM International Conference on Multimedia System (MMSys 2016)},
	year = {2016},
	publisher = {ACM},
	abstract = {This demonstration will showcase mixed reality technologies that we developed for a series of public art performances in Vienna in October 2015 in a collaboration of performance artists and researchers. The focus of the demonstration is on natural interaction techniques that can be used intuitively to control an avatar in a virtual 3D world. We combine virtual reality devices with optical location tracking, hand gesture recognition and smart devices. Conference attendees will be able to walk around in a Minecraft world by physically moving in the real world and to perform actions on virtual world items using hand gestures. They can also test our initial system for shared avatar control, in which a user in the real world cooperates with a user in the virtual world. Finally, attendees will have the opportunity to give us feedback about their experience with our system.},
	doi = {10.1145/2910017.2910632},
	author = {Loviska, Milan and Krause, Otto and Herman A. {Engelbrecht} and Jason B. {Nel} and Schiele, Gregor and Burger, Alwyn and Schmei{\ss}er, Stephan and Cichiwskyj, Christopher and Calvet, Lilian and Griwodz, Carsten and Halvorsen, P{\r a}l}
}
@inproceedings {24475,
	title = {LIRE - Open Source Visual Information Retrieval},
	journal = {Multimedia System Conference 2016},
	year = {2016},
	month = {05/2016},
	publisher = {ACM},
	address = {New York},
	author = {Lux, Mathias and Riegler, Michael and Pogorelov, Konstantin and Halvorsen, P{\r a}l and Anagnostopoulos, Nektarios}
}
@inproceedings {24857,
	title = {The MediaEval 2016 Context of Experience Task: Recommending Videos Suiting a Watching Situation},
	journal = {MediaEval 2016 Workshop},
	year = {2016},
	month = {10/2016},
	publisher = {CEUR Workshop Proceedings},
	address = {Hilversum, Netherlands},
	abstract = {In this paper we present an overview of the Context of Experience Task: recommending videos suiting a watching situation which is part of the MediaEval 2016 Benchmark. The aim of the task is to explore multimedia content that is watched under a certain situation. The scope of the this years task lies on movies watched during a flight. We hypothesize that users will have different preferences for movies that are watched during a flight compared to when a movie is watched at home or the cinema. This is most probably influenced by the context and the devices used to watch. In the case of being on a flight, the context is clearly different to normal situation (noise, compact, bad air) and also the devices differ (small screens, bad audio quality). The main goal of the task is to estimate if a person would like to watch a certain movie on the airplane or not. As dataset we provide a large collection of movies, collected from an airline, including pre-extracted visual, text and audio features.},
	author = {Riegler, Michael and Spampinato, Concetto and Griwodz, Carsten and Halvorsen, P{\r a}l}
}
@inproceedings {24641,
	title = {Multimedia and Medicine: Teammates for Better Disease Detection and Survival},
	journal = {ACM Multimedia},
	year = {2016},
	month = {10/2016},
	publisher = {ACM},
	address = {Amsterdam, The Netherlands, The Netherlands},
	doi = {http://dx.doi.org/10.1145/2964284.2976760},
	author = {Riegler, Michael and Griwodz, Carsten and Spampinato, Concetto and de Lange, Thomas and Sigrun L. {Eskeland} and Pogorelov, Konstantin and Tavanapong, Wallapak and Peter Thelin {Schmidt} and Gurrin, Cathal and Johansen, Dag and Johansen, H{\r a}vard and Halvorsen, P{\r a}l}
}
@inproceedings {24642,
	title = {OpenVQ - A Video Quality Assessment Toolkit},
	journal = {ACM Multimedia},
	year = {2016},
	month = {10/2016},
	publisher = {ACM},
	address = {Amsterdam, The Netherlands, The Netherlands},
	doi = {http://dx.doi.org/10.1145/2964284.2973800},
	author = {Skarseth, Kristian and Bj{\o}rlo, Henrik and Halvorsen, P{\r a}l and Riegler, Michael and Griwodz, Carsten}
}
@book {25091,
	title = {Proceedings of the 8th International Workshop on Mobile Video (MoVid{\textquoteright}16)},
	year = {2016},
	publisher = {ACM Digital Library},
	isbn = {978-1-4503-4356-5},
	author = {Han, Qi and Halvorsen, P{\r a}l}
}
@inproceedings {24473,
	title = {Right inflight? A dataset for exploring the automatic prediction of movies suitable for a watching situation},
	journal = {Multimedia Systems Conference 2016},
	year = {2016},
	month = {05/2016},
	publisher = {ACM},
	address = {New York},
	author = {Riegler, Michael and Spampinato, Concetto and Halvorsen, P{\r a}l and Lux, Mathias and Markussen, Jonas and Pogorelov, Konstantin and Griwodz, Carsten and H{\r a}kon Kvale {Stensland}}
}
@inproceedings {24961,
	title = {Robustness of 3D Point Positions to Camera Baselines in Markerless AR Systems},
	journal = {The 7th ACM International Conference on Multimedia System (MMSys 2016)},
	year = {2016},
	publisher = {ACM},
	abstract = {\&nbsp;In the Augmented Reality (AR) applications, high quality relates to an accurate augmentation of virtual objects in the real scene. This can be accomplished only if the position of the observer is accurately known. This boils down to solving image-based location problem by an accurate camera pose (relative position and orientation) estimation, when a stereo or multiple camera setup is used. Consider a relevant appli- cation scenario as in a movie production set, where the di- rector is able to preview a scene as an integrated view of the real scene augmented with animated 3D models. The main camera shoots the scene, where as secondary stereo camera pair is used for image registration and localization. The di- rector can view the integrated preview from any viewpoint perfectly, as long as the camera pose estimation is accurate.Moreover, in the case of a markerless AR system, the chal- lenge for camera pose estimation, is strongly influenced by the precision of detected feature correspondences between the images. Unfortunately, several of the state-of-art fea- ture extractors (detectors and descriptors) cannot guarantee a consistent accuracy of camera pose estimation, especially at varied camera baselines (viewpoints). As a consequence, the precise augmentation of objects, as desired in an AR application, is compromised. Hence, it becomes necessary to understand the magnitude of this error in relation to the camera baseline depending on the chosen feature extractors.We, therefore, assess the quality of the position and the orientation of 3D reconstruction by evaluating 26 feature extractor combinations over 50 different camera baselines. To be directly relevant for AR applications, we evaluate by measuring the reconstruction error in 3D space, instead of re-projection error in 2D space. After the experiment, we have found the SIFT and KAZE feature extractors to be highly accurate and more robust to large camera baselines than others. Importantly, as a result of our study, we provide a recommendation for system builders to help them make a better choice of the feature extractor and/or the camera density required for their application.\&nbsp;},
	doi = {http://dx.doi.org/10.1145/2910017.2910611},
	author = {Dwarakanath, Deepak and Griwodz, Carsten and Halvorsen, P{\r a}l}
}
@inproceedings {24858,
	title = {Simula @ MediaEval 2016 Context of Experience Task},
	journal = {MediaEval 2016 Workshop},
	year = {2016},
	month = {10/2016},
	publisher = {CEUR Workshop Proceedings},
	address = {Hilversum, Netherlands},
	abstract = {This paper presents our approach for the Context of Multimedia Experience Task of the MediaEval 2016 Benchmark. We present different analyses of the given data using different subsets of data sources and combinations of it. Our approach gives a baseline evaluation indicating that metadata approaches work well but that also visual features can provide useful information for the given problem to solve.},
	author = {Pogorelov, Konstantin and Riegler, Michael and Halvorsen, P{\r a}l and Griwodz, Carsten}
}
@article {24540,
	title = {Tiling in Interactive Panoramic Video: Approaches and Evaluation},
	journal = {IEEE Transactions on Multimedia},
	volume = {18},
	year = {2016},
	pages = {1819-1831},
	publisher = {IEEE},
	abstract = {Interactive panoramic systems are currently on therise. However, one of the major challenges in such a system isthe overhead involved in transferring a full-quality panoramato the client when only a part of the panorama is used toextract a virtual view. Thus, such a system should maximize theuser experience while simultaneously minimizing the bandwidthrequired. In this paper, we apply tiling to deliver different qualitylevels for different parts of the panorama. Tiling has traditionallybeen applied to the delivery of very high-resolution content toclients. Here, we apply similar ideas in a real-time interactivepanoramic video system. A major challenge lies in the movementof such a virtual view, for which clients\&rsquo; regions of interestchange dynamically and independently from each other. Weshow that our algorithms, which progressively increase in qualitytowards the point of the view, manage to (i) reduce the bandwidthrequirement and (ii) provide a similar QoE compared to a fullpanorama system.},
	author = {Vamsidhar Reddy {Gaddam} and Riegler, Michael and Eg, Ragnhild and Griwodz, Carsten and Halvorsen, P{\r a}l}
}
@article {Simula.simula.2804,
	title = {Audiovisual robustness: Exploring perceptual tolerance to asynchrony and quality distortion},
	journal = {Multimedia Tools and Applications},
	volume = {74},
	year = {2015},
	pages = {345-365},
	publisher = {Springer},
	abstract = {Rules-of-thumb for noticeable and detrimental asynchrony between audio and video streams have long since been established from the contributions of several studies. Although these studies share similar findings, none have made any discernible assumptions regarding audio and video quality. Considering the use of active adaptation in present and upcoming streaming systems, audio and video will continue to be delivered in separate streams; consequently, the assumption that the rules-of-thumb hold independent of quality needs to be challenged. To put this assumption to the test, we focus on the detection, not the appraisal, of asynchrony at different levels of distortion. Cognitive psychologists use the term temporal integration to describe the failure to detect asynchrony. The term refers to a perceptual process with an inherent buffer for short asynchronies, where corresponding auditory and visual signals are merged into one experience. Accordingly, this paper discusses relevant causes and concerns with regards to asynchrony, it introduces research on audiovisual perception, and it moves on to explore the impact of audio and video quality on the temporal integration of different audiovisual events. Three content types are explored, speech from a news broadcast, music presented by a drummer, and physical action in the form of a chess game. Within these contexts, we found temporal integration to be very robust to quality discrepancies between the two modalities. In fact, asynchrony detection thresholds varied considerably more between the different content than they did between distortion levels. Nevertheless, our findings indicate that the assumption concerning the independence of asynchrony and audiovisual quality may have to be reconsidered.},
	keywords = {Workshop},
	author = {Eg, Ragnhild and Griwodz, Carsten and Halvorsen, P{\r a}l and Dawn Marie {Behne}}
}
@article {23628,
	title = {Cache-Centric Video Recommendation: An Approach to Improve the Efficiency of YouTube Caches},
	journal = {ACM Trans. Multimedia Comput. Commun. Appl.},
	volume = {11},
	year = {2015},
	month = {06/2015},
	pages = {1--20},
	publisher = {ACM},
	address = {New York, NY, USA},
	abstract = {In this article, we take advantage of the user behavior of requesting videos from the top of the related list provided by YouTube to improve the performance of YouTube caches. We recommend that local caches reorder the related lists associated with YouTube videos, presenting the cached content above noncached content. We argue that the likelihood that viewers select content from the top of the related list is higher than selection from the bottom, and pushing contents already in the cache to the top of the related list would increase the likelihood of choosing cached content. To verify that the position on the list really is the selection criterion more dominant than the content itself, we conduct a user study with 40 YouTube-using volunteers who were presented with random related lists in their everyday YouTube use. After confirming our assumption, we analyze the benefits of our approach by an investigation that is based on two traces collected from a university campus. Our analysis shows that the proposed reordering approach for related lists would lead to a 2 to 5 times increase in cache hit rate compared to an approach without reordering the related list. This increase in hit rate would lead to reduction in server load and backend bandwidth usage, which in turn reduces the latency in streaming the video requested by the viewer and has the potential to improve the overall performance of YouTube{\textquoteright}s content distribution system. An analysis of YouTube{\textquoteright}s recommendation system reveals that related lists are created from a small pool of videos, which increases the potential for caching content from related lists and reordering based on the content in the cache.},
	keywords = {Caching, recommendation, YouTube},
	issn = {1551-6857},
	doi = {10.1145/2716310},
	url = {http://doi.acm.org/10.1145/2716310},
	author = {Dilip Kumar {Krishnappa} and Zink, Michael and Griwodz, Carsten and Halvorsen, P{\r a}l}
}
@article {23367,
	title = {The Cameraman Operating My Virtual Camera Is Artificial: Can The Machine Be As Good As A Human?},
	journal = {ACM Transactions on Multimedia Computing, Communications and Applications},
	volume = {11},
	year = {2015},
	month = {06/2015},
	pages = {56:1--56:20},
	publisher = {ACM},
	address = {New York, NY, USA},
	abstract = {In this paper, we argue that the energy spent in designing autonomous camera control systems is not spent in vain. We present a real-time virtual camera system that can create smooth camera motion. Similar systems are frequently benchmarked with the human operator as the best possible reference; however, we avoid a priori assumptions in our evaluations. Our main question is simply whether we can design algorithms to steer a virtual camera that can compete with the user experience for recordings from an expert operator with several years of experience? In this respect, we present two low-complexity servoing methods that are explored in two user studies. The results from the user studies give a promising answer to the question pursued. Furthermore, all components of the system meet the real-time requirements on commodity hardware. The growing capabilities of both hardware and network in mobile devices give us hope that this system can be deployed to mobile users in the near future. Moreover, the design of the presented system takes into account that services to concurrent users must be supported.},
	issn = {1551-6857},
	doi = {10.1145/2744411},
	url = {http://doi.acm.org/10.1145/2744411},
	author = {Vamsidhar Reddy {Gaddam} and Eg, Ragnhild and Langseth, Ragnar and Griwodz, Carsten and Halvorsen, P{\r a}l}
}
@misc {23459,
	title = {Energy and Performance Optimization of a Simple Video Encoder on the Jetson--TK1},
	howpublished = {GPU Technology Conference 2015},
	year = {2015},
	month = {03/2015},
	publisher = {Nvidia},
	abstract = {This poster analyses the energy consumption of a simple video encoder running on NVIDIA\&$\#$39;s Tegra K1 processor. The total energy consumption of the video encoder is investigated under the influence of different hardware configurations, such as which processors (CPU clusters or GPU) are used, DVFS algorithms, and whether performance optimisations like NEON are implemented. We find that NEON instructions and multithreading generally have positive effects on energy consumption, saving between 25 to 40 \% energy compared to a non\&shy;optimised, naive implementation. GPU offloading is found to be marginally better than CPU execution by an amount of 1.7 \%.},
	url = {http://on-demand.gputechconf.com/gtc/2015/posters/GTC_2015_Embedded_Systems_01_P5193_WEB.pdf},
	author = {Kristoffer Robin {Stokke} and H{\r a}kon Kvale {Stensland} and Halvorsen, P{\r a}l}
}
@inproceedings {23461,
	title = {Energy Efficient Continuous Multimedia Processing Using the Tegra K1 Mobile SoC},
	journal = {Proceedings of the 7th ACM International Workshop on Mobile Video (MoVid)},
	year = {2015},
	month = {03/2015},
	pages = {15-16},
	publisher = {ACM},
	abstract = {Energy consumption is an important issue for mobile devices,\&nbsp;as the technological development in battery technology\&nbsp;has not kept pace with the power requirements of mobile\&nbsp;hardware. In this paper, we use a video rotation filter\&nbsp;to study the efects of CPU and GPU frequency scaling in\&nbsp;terms of performance and energy. Our platform is the Tegra\&nbsp;K1 mobile processor with a quad-core CPU and a CUDA capable\&nbsp;GPU. We find that most energy can be saved by\&nbsp;minimising CPU frequency while meeting the filter\&rsquo;s framerate\&nbsp;requirement. Interestingly, the frequency scaling affects\&nbsp;GPUs differently, where the best frequency is always moderately\&nbsp;higher than the minimum which meets the framerate\&nbsp;requirement. Using these heuristics, it is possible to save up\&nbsp;to 10 \% energy compared to the standard Linux frequency\&nbsp;scaling algorithms, which use processor utilisation to adjust\&nbsp;processor frequency.},
	isbn = {978-1-4503-3353-5},
	doi = {10.1145/2727040.2727044},
	url = {http://dl.acm.org/citation.cfm?id=2727044},
	author = {Kristoffer Robin {Stokke} and H{\r a}kon Kvale {Stensland} and Griwodz, Carsten and Halvorsen, P{\r a}l}
}
@inproceedings {23462,
	title = {Energy Efficient Video Encoding Using the Tegra K1 Mobile Processor [Demo Paper]},
	journal = {Proceedings of the 6th ACM Multimedia Systems Conference (MMSys)},
	year = {2015},
	month = {03/2015},
	publisher = {ACM},
	abstract = {Energy consumption is an important concern for mobile devices,\&nbsp;where the evolution in battery storage capacity has\&nbsp;not followed the power usage requirements of modern hardware.\&nbsp;However, innovative and flexible hardware platforms\&nbsp;give developers better means of optimising the energy consumption\&nbsp;of their software. For example, the Tegra K1\&nbsp;System-on-Chip (SoC) offers two CPU clusters, GPU offloading,\&nbsp;frequency scaling and other mechanisms to control\&nbsp;the power and performance of applications. In this demonstration,\&nbsp;the scenario is live video encoding, and participants\&nbsp;can experiment with power usage and performance using the\&nbsp;Tegra K1\&rsquo;s hardware capabilities. A popular power-saving\&nbsp;approach is a \&ldquo;race to sleep\&rdquo; strategy where the highest CPU\&nbsp;frequency is used while the CPU has work to do, and then\&nbsp;the CPU is put to sleep. Our own experiments indicate that\&nbsp;an energy reduction of 28 \% can be achieved by running\&nbsp;the video encoder on the lowest CPU frequency at which\&nbsp;the platform achieves an encoding frame rate equal to the\&nbsp;minimum frame rate of 25 Frames Per Second (FPS).},
	isbn = {978-1-4503-3351-1},
	doi = {10.1145/2713168.2713186},
	url = {http://dl.acm.org/citation.cfm?id=2713186},
	author = {Kristoffer Robin {Stokke} and H{\r a}kon Kvale {Stensland} and Griwodz, Carsten and Halvorsen, P{\r a}l}
}
@article {23460,
	title = {An Experimental Evaluation of Debayering Algorithms on GPUs for Recording Panoramic Video in Real-time},
	journal = {International Journal of Multimedia Data Engineering and Management (IJMDEM)},
	volume = {6},
	year = {2015},
	month = {07/2015},
	pages = {1-16},
	publisher = {IGI Global},
	abstract = {Modern video cameras often only capture a single color per pixel\&nbsp;in a single pass operation. This process is called ltering, where pixels\&nbsp;are ltered through a color lter array, and the Bayer filter is perhaps\&nbsp;the most common filter used today. This means that we must restore\&nbsp;the missing color channels in the image or the video frame in a post-processing step, i.e., a process referred to as debayering. In a live\&nbsp;video scenario, this operation must be performed eciently in order\&nbsp;to output each video frame in real-time, while also yielding acceptable\&nbsp;visual quality. Here, we evaluate debayering algorithms implemented\&nbsp;on a GPU for real-time panoramic video recordings using multiple\&nbsp;2K-resolution cameras.},
	issn = {1947-8534},
	doi = {10.4018/ijmdem.2015070101},
	author = {Langseth, Ragnar and Vamsidhar Reddy {Gaddam} and H{\r a}kon Kvale {Stensland} and Griwodz, Carsten and Halvorsen, P{\r a}l and Johansen, Dag}
}
@inproceedings {albisser2015annotation,
	title = {Expert Driven Semi-Supervised Elucidation Tool for Medical Endoscopic Videos},
	journal = {Proceedings of the 6th ACM Multimedia Systems Conference},
	year = {2015},
	month = {03/2015},
	publisher = {ACM},
	author = {Albisser, Zeno and Riegler, Michael and Halvorsen, P{\r a}l and Zhou, Jiang and Griwodz, Carsten and Balasingham, Ilangko and Gurrin, Cathal}
}
@inproceedings {23358,
	title = {Exploitation of Producer Intent in Relation to Bandwidth and QoE for Online Video Streaming Services},
	journal = {NOSSDAV at Multimedia Systems Conference },
	year = {2015},
	month = {03/2015},
	publisher = {ACM},
	address = {Portland, USA},
	abstract = {This paper is the product of recent advances in research on users{\textquoteright} intent during multimedia content retrieval. Our goal is to save bandwidth while streaming video clips from a browsable on-demand service, while maintaining or even improving the users{\textquoteright} quality of experience (QoE). Understanding user intent allows us to predict whether streaming a particular video in a low quality constitutes a reduced QoE for a user. However, many VoD streaming services today are used by users for a wide variety of reasons, meaning that user intent cannot be inferred from their use of the service alone. However, our investigation demonstrates that user intent does in most cases coincide with producer intent. We can also demonstrate that the latter can be inferred from the content itself as well as associated metadata. By transitivity, we can choose a default video quality that satisfies the users QoE in the majority of cases.\&nbsp;},
	author = {Riegler, Michael and Calvet, Lilian and Calvet, Amandine and Halvorsen, P{\r a}l and Griwodz, Carsten}
}
@inproceedings {23569,
	title = {Introduction to a Task on Context of Experience: Recommending Videos Suiting a Watching Situation},
	journal = {MediaEval Benchmarking Initiative for Multimedia Evaluation},
	year = {2015},
	month = {09/2015},
	publisher = {CEUR Workshop Proceedings},
	address = {Wurzen, Germany},
	author = {Riegler, Michael and Spampinato, Concetto and Markussen, Jonas and Halvorsen, P{\r a}l and Griwodz, Carsten}
}
@inproceedings {23716,
	title = {Latency and Fairness Trade-Off for Thin Streams Using Redundant Data Bundling in TCP},
	journal = {IEEE 40th Conference on Local Computer Networks (LCN)},
	year = {2015},
	month = {10/2015},
	pages = {287-294},
	publisher = {IEEE},
	address = {Clearwater Beach, FL, USA},
	abstract = {Time-dependent applications using TCP often send thin-stream traffic, characterised by small packets and high inter-transmission-times. Retransmissions after packet loss can result in very high delays for such flows as they often cannot trigger fast retransmit. Redundant Data Bundling is a mechanism that preempts the experience of loss for a flow by piggybacking unacknowledged segments with new data as long as the total packet size is lower than the flow maximum segment size. Although successful at reducing retransmission latency, this mechanism had design issues leaving it open for abuse, effectively making it unsuitable for general Internet deployment. In this paper, we have redesigned the RDB mechanism to make it safe for deployment. We improve the trigger for when to apply it and evaluate its fairness towards competing traffic. Extensive experimental results confirm that our proposed modifications allows for inter-flow fairness while maintaining the significant latency reductions from the original RDB mechanism.},
	keywords = {communication, latency, networks, thin streams},
	doi = {10.1109/LCN.2015.7366322},
	author = {Bendik R. {Opstad} and Markussen, Jonas and Ahmed, Iffat and Petlund, Andreas and Griwodz, Carsten and Halvorsen, P{\r a}l}
}
@inproceedings {24570,
	title = {A Logical Memory Model for Scaling Parallel Multimedia Workloads},
	journal = {Network and Operating Systems Support for Digital Audio and Video (NOSSDAV)},
	year = {2015},
	pages = {49-54},
	publisher = {ACM},
	address = {New York, NY, USA},
	keywords = {cache, coherency, cpu, false sharing, multicore, programming, scalability},
	isbn = {978-1-4503-3352-8},
	doi = {10.1145/2736084.2736096},
	url = {http://doi.acm.org/10.1145/2736084.2736096},
	author = {Preben N. {Olsen} and Nyhus, Martin and Halvorsen, P{\r a}l and Griwodz, Carsten}
}
@inproceedings {23526,
	title = {Online Re-calibration for Robust 3D Measurement Using Single Camera-PantoInspect Train Monitoring System},
	journal = {Proceedings of the International Conference on Computer Vision Systems (ICVS) - Lecture Notes in Computer Science Volume 9163},
	year = {2015},
	publisher = {Lecture Notes in Computer Science, Springer.Verlag},
	abstract = {Vision-based inspection systems measures defects accurately with the help of a checkerboard calibration (CBC) method. However, the 3D measurements of such systems are prone to errors, caused by physical misalignment of the object-of-interest and noisy image data. The PantoInspect Train Monitoring System (PTMS), is one such system that inspects defects on pantographs mounted on top of the electric trains. In PTMS, the measurement errors can compromise railway safety. Although this problem can be solved by re-calibrating the cameras, the process involves manual intervention leading to large servicing times. Therefore, in this paper, we propose Feature Based Calibration (FBC) in place of CBC, to cater an obvious need for online re-calibration that enhances the usability of the system. FBC involves feature extraction, pose estimation, back-projection of defect points and estimation of 3D measurements. We explore four state-of-the-art pose estimation algorithms in FBC using very few feature points. This paper evaluates and discusses the performance of FBC and its robustness against practical problems, in comparison to CBC. As a result, we identify the best FBC algorithm type and operational scheme for PTMS. In conclusion, we show that, by adopting FBC in PTMS and other related 3D systems, better performance and robustness can be achieved compared to CBC.\&nbsp;},
	doi = {10.1007/978-3-319-20904-3_45},
	author = {Dwarakanath, Deepak and Griwodz, Carsten and Halvorsen, P{\r a}l and Lildballe, Jacob}
}
@inproceedings {23432,
	title = {Playing Around the Eye Tracker - A Serious Game Based Dataset},
	journal = {Second International Workshop on Gamification for Information Retrieval (GamifIR{\textquoteright}15) },
	year = {2015},
	month = {03/2015},
	publisher = {CEUR Workshop Proceedings},
	address = {Vienna, Austria},
	abstract = {In this paper we present a dataset of visual saliency segments\&nbsp;associated to social images, collected through a mobile game\&nbsp;in conjunction with a crowdsourcing campaign. Our data\&nbsp;are collected in the game itself, where players guess what\&nbsp;is depicted in a gradually uncovered image. The game mechanics\&nbsp;allow us to collect information about which image\&nbsp;segments are required by the user to correctly recover the\&nbsp;image content. The provided dataset can be applied to both,\&nbsp;computer vision and image retrieval algorithms, and it aims\&nbsp;to contribute to the understanding of human visual perception\&nbsp;and attention. Moreover, the end objective is to test the\&nbsp;game as a potential substitute to professional eye tracking\&nbsp;systems.},
	author = {Riegler, Michael and Eg, Ragnhild and Calvet, Lilian and Halvorsen, P{\r a}l and Griwodz, Carsten}
}
@book {23489,
	title = {Proceedings of the 7th ACM International Workshop on Mobile Video (MOVID{\textquoteright}15)},
	year = {2015},
	publisher = {ACM},
	address = {ACM},
	abstract = {We welcome you to the seventh ACM Workshop on Mobile Video (MoVid), held in conjunction with ACM Multimedia Systems (MMSys) 2015 Conference on March 18-20, 2015 in Portland, Oregon, USA. The workshop is sponsored by ACM SIGMM and in cooperation with SIGOPS and SIGCOMM.The mission of the MoVid workshop series is to deepen the understanding of research and deployment challenges in building the Next Generation Mobile Video technologies. The MoVid workshop series aims to address multiple aspects of delivering visually-rich applications to mobile users. This year{\textquoteright}s workshop continues this tradition of presentation of novel research results and experimental reports on cutting edge issues of mobile video applications. MoVid 2015 gives researchers and practitioners a unique opportunity to share their perspectives with others who are interested in various aspects of mobile multimedia. In this respect, MoVid 2015 features a half-day workshop with a keynote, two regular paper sessions and a joint panel with NOSSDAV.},
	isbn = {978-1-4503-3353-5},
	url = {http:://dl.acm.org/citation.cfm?id=2727040\&coll=DL\&dl=GUIDE\&CFID=491604530\&CFTOKEN=27719602},
	editor = {Halvorsen, P{\r a}l and Dutt, Nikil}
}
@inproceedings {23370,
	title = {Scaling Virtual Camera Services to a Large Number of Users},
	journal = {Proceedings of the 6th annual ACM conference on Multimedia Systems (MMSYS)},
	year = {2015},
	month = {03/2015},
	pages = {93-96},
	publisher = {ACM},
	address = {New York, NY, USA},
	abstract = {By processing video footage from a camera array, one can easily make\&nbsp;wide-field-of-view panorama videos. From the single panorama video,\&nbsp;one can further generate multiple virtual cameras supporting\&nbsp;personalized views to a large number of users based on only the few\&nbsp;physical cameras in the array. However, giving personalized services to large\&nbsp;numbers of users potentially introduces both bandwidth and processing\&nbsp;bottlenecks, depending on where the virtual camera is processed.In this demonstration, we present a system that address the large cost\&nbsp;of transmitting entire panorama video to the end-user where the user\&nbsp;creates the virtual views on the client device. Our approach is to\&nbsp;divide the panorama into tiles, each encoded in multiple\&nbsp;qualities. Then, the panorama video tiles are retrieved by the client\&nbsp;in a quality (and thus bit rate) depending on where the virtual camera\&nbsp;is pointing, i.e., the video quality of the tile changes dynamically\&nbsp;according to the user interaction. Our initial experiments indicate\&nbsp;that there is a large potential of saving bandwidth on the cost of\&nbsp;trading quality of in areas of the panorama frame not used for the\&nbsp;extraction of the virtual view.\&nbsp;},
	isbn = { 978-1-4503-3351-1},
	author = {Vamsidhar Reddy {Gaddam} and Langseth, Ragnar and H{\r a}kon Kvale {Stensland} and Griwodz, Carsten and Johansen, Dag and Halvorsen, P{\r a}l}
}
@inproceedings {23717,
	title = {TADA: An Active Measurement Tool for Automatic Detection of AQM},
	journal = {Valuetools 2015, Proceedings of the 9th EAI International Conference on Performance Evaluation Methodologies and Tools},
	year = {2015},
	author = {Minoo Kargar {Bideh} and Petlund, Andreas and Griwodz, Carsten and Ahmed, Iffat and Halvorsen, P{\r a}l and Behjati, Razieh and Brunstr{\"o}m, Anna and Alfredsson, Stefan}
}
@inproceedings {23535,
	title = {Tiling of Panorama Video for Interactive Virtual Cameras: Overheads and Potential Bandwidth Requirement Reduction},
	journal = {21st International Packet Video Workshop (PV 2015)},
	year = {2015},
	month = {06/2015},
	publisher = {IEEE},
	abstract = {Delivering high resolution, high bitrate panoramavideo to a large number of users introduces huge scalingchallenges. To reduce the resource requirement, researchers haveearlier proposed tiling in order to deliver different qualities indifferent spatial parts of the video. In our work, providing aninteractive moving virtual camera to each user, tiling may be usedto reduce the quality depending on the position of the virtualview. This raises new challenges compared to existing tilingapproaches as the need for high quality tiles dynamically change.In this paper, we describe a tiling approach of panorama videofor interactive virtual cameras where we provide initial resultsshowing the introduced overheads and the potential reduction inbandwidth requirement.\&nbsp;},
	author = {Vamsidhar Reddy {Gaddam} and Hoang Bao {Ngo} and Langseth, Ragnar and Griwodz, Carsten and Johansen, Dag and Halvorsen, P{\r a}l}
}
@article {23471,
	title = {Using a Commodity Hardware Video Encoder for Interactive Applications},
	journal = {International Journal of Multimedia Data Engineering and Management (IJMDEM)},
	volume = {6},
	year = {2015},
	month = {07/2015},
	pages = {17-31},
	publisher = {IGI Global},
	abstract = {Over the last years, video streaming has become one of the most dominant Internet services. Due to the increased availability of high-speed Internet access, multimedia services are becoming more interactive. Examples of such applications are both cloud gaming and systems where users can interact with high-resolution content. During the last few years, programmable hardware video encoders have been built into commodity hardware such as CPUs and GPUs. We evaluate one of these encoders in a scenario where we have individual streams delivered to the end users. Our results show that the visual video quality and the frame size of the hardware-based encoder are comparable to a software-based approach. To evaluate a complete system, we have implemented our proposed streaming pipeline into Quake III. We found that running the game on a remote server and streaming the video output to a client web browser located in a typical home environment is possible and enjoyable. The interaction latency is measured to be less than 90 ms, which is below what is reported for OnLive in a similar environment},
	issn = {1947-8534},
	doi = {10.4018/ijmdem.2015070102},
	author = {H{\r a}kon Kvale {Stensland} and Martin Alexander {Wilhelmsen} and Vamsidhar Reddy {Gaddam} and Mortensen, Asgeir and Langseth, Ragnar and Griwodz, Carsten and Halvorsen, P{\r a}l}
}
@inproceedings {23566,
	title = {Why Design Matters - Crowdsourcing of Complex Tasks},
	journal = {ACM CrowdMM},
	year = {2015},
	month = {10/2015},
	publisher = {ACM},
	address = {Brisbane, Australia},
	abstract = {In this paper, we show how the power of the crowd can be usedto do complex tasks using human pose estimation as a use case.Crowdsourcing tasks are usually not very complex and easy tosolve by workers that are not experienced in a certain topic. Formore complex tasks, it is general recommended to use experiencedworkers or experts. However, we show that tasks can also be morecomplex for non-expert workers and that they produce data that isclose to what experts would report. Therefore, a detailed descriptionof the crowdsourcing campaign, the methods applied and theresults will be given, and we discuss how the obtained data can beused.},
	keywords = {Annotation, Crowdsourcing, Multimedia},
	doi = {http://dx.doi.org/10.1145/2810188.2810190},
	author = {Winther, B{\r a}rd and Riegler, Michael and Griwodz, Carsten and Halvorsen, P{\r a}l},
	editor = {Calvet, Lilian}
}
@inproceedings {23833,
	title = {Why Race-to-Finish is Energy-Inefficient for Continuous Multimedia Workloads},
	journal = {Proceedings of the 9th IEEE International Symposium on Embedded Multicore/Many-core Systems-on-Chip (MCSoC)},
	year = {2015},
	month = {09/2015},
	pages = {57-64},
	publisher = {IEEE},
	abstract = {It is often believed that a \&quot;race-to-finish\&quot; approach, where processing is finished quickly, is the best way to conserve energy on modern mobile architectures. However, from earlier work we know that for continuous multimedia workloads, the best way to conserve energy is to minimise processor frequency such that application deadlines are met. In this paper, we investigate the reasons behind this. We develop an original method to model dynamic and static power on individual power rails of the Tegra K1 by only measuring the total power usage of the board. Our model has an average error of only 8 \%. We find that the way an application scales performance with frequency is very important for energy efficiency. We demonstrate a 37 \% energy saving by minimising processor and memory frequency of a video processing filter such that a framerate of 20 FPS is met.},
	doi = {10.1109/MCSoC.2015.20},
	url = {http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7328187},
	author = {Kristoffer Robin {Stokke} and H{\r a}kon Kvale {Stensland} and Halvorsen, P{\r a}l and Griwodz, Carsten}
}
@article {19142,
	title = {Adaptive Media Streaming to Mobile Devices: Challenges, Enhancements, and Recommendations},
	journal = {Advances in Multimedia},
	volume = {2014},
	year = {2014},
	pages = {1{\textendash}21},
	publisher = {Hindawi},
	issn = {1687-5680},
	doi = {10.1155/2014/805852},
	url = {http://www.hindawi.com/journals/am/2014/805852/},
	author = {Kupka, Tomas and Riiser, Haakon and Ni, Pengpeng and Eg, Ragnhild and Griwodz, Carsten and Halvorsen, P{\r a}l}
}
@inproceedings {Simula.simula.2654,
	title = {Analysis of SR ARQ Delays Using Data-Bundling Over Markov Channels},
	journal = {The Nineteenth IEEE Symposium on Computers and Commuications (IEEE ISCC)},
	year = {2014},
	month = {June},
	publisher = {IEEE},
	type = {Conference},
	abstract = {Data-bundling is a useful technique that decreases the delivery delay of packet streams when they are transmitted over noisy channels and are subject to retransmission-based error control. In this paper, we investigate the packet delay statistics for a fully reliable selective repeat automatic repeat request (SR ARQ) where a data-bundling mechanism is employed. In more detail, we discuss a model for data-bundling to analyze the SR ARQ mechanism over wireless channels based on Markov chains. We evaluate various channel error distributions and analyze the buffer occupancy to check if the data-bundling mechanism provides efficient results. We further analyze the queueing, delivery and overall delay statistics at link layer. We found that using data-bundling can improve the delay performance of the SR ARQ mechanism, especially when bursty channels with heavily correlated errors are considered. Thus, this technique can bring useful improvements for real-time services, multimedia, and other delay-sensitive applications over wireless networks.},
	keywords = {Conference},
	author = {Ahmed, Iffat and Badia, Leonardo and Petlund, Andreas and Griwodz, Carsten and Halvorsen, P{\r a}l},
	editor = {Sahni, Sartaj}
}
@inproceedings {mmsys.2014-02-12.3999932578,
	title = {Automatic Event Extraction and Video Summaries From Soccer Games},
	journal = {Proceedings of the 5th annual ACM conference on Multimedia Systems (MMSYS)},
	year = {2014},
	month = {March},
	publisher = {ACM},
	type = {Conference},
	abstract = {Bagadus is a prototype of a soccer analysis application which integrates a sensor system, a video camera array and soccer analytics annotations. The current prototype is installed at Alfheim Stadium in Norway, and provides a large set of new functions compared to existing solutions. One important feature is to automatically extract video events and sum- maries from the games, i.e., an operation that traditionally consumes a huge amount of time. In this demo, we demon- strate how our integration of subsystems enable several types of summaries to be generated automatically, and we show that the video summaries are displayed with a response time around one second.},
	doi = {10.1145/2557642.2579374},
	author = {Mortensen, Asgeir and Vamsidhar Reddy {Gaddam} and H{\r a}kon Kvale {Stensland} and Griwodz, Carsten and Johansen, Dag and Halvorsen, P{\r a}l}
}
@inproceedings {Mortensen2014a,
	title = {Automatic event extraction and video summaries from soccer games},
	journal = {Proceedings of the 5th ACM Multimedia Systems Conference on - MMSys {\textquoteright}14},
	year = {2014},
	pages = {176{\textendash}179},
	publisher = {ACM Press},
	address = {New York, New York, USA},
	isbn = {9781450327053},
	doi = {10.1145/2557642.2579374},
	url = {http://dl.acm.org/citation.cfm?doid=2557642.2579374},
	author = {Mortensen, Asgeir and Vamsidhar Reddy {Gaddam} and H{\r a}kon Kvale {Stensland} and Griwodz, Carsten and Halvorsen, P{\r a}l}
}
@inproceedings {Simula.simula.2536,
	title = {Automatic Exposure for Panoramic Systems in Uncontrolled Lighting Conditions: a Football Stadium Case Study},
	journal = {The Engineering Reality of Virtual Reality},
	year = {2014},
	publisher = {SPIE},
	type = {Conference},
	abstract = {One of the most common ways of capturing wide field-of-view scenes like arena sports is by capturing panoramic videos. Several experiments were conducted in order to devise an approach for driving a panorama video capture system in a completely automatic fashion. The target scene is an outdoor football stadium, where the light is uncontrolled and widely varying owing to the weather. This paper provides in detail various attempted approaches and the outcomes. Several papers propose global color correction for adjusting the colors, yet practically such a correction introduces new artifacts into the video streams. It is observed that visually pleasing results are obtaining by appropriate synchronization of exposure settings.},
	keywords = {Conference},
	author = {Vamsidhar Reddy {Gaddam} and Griwodz, Carsten and Halvorsen, P{\r a}l}
}
@inproceedings {acmmm2014demo,
	title = {Automatic Real-Time Zooming and Panning on Salient Objects From a Panoramic Video},
	journal = {ACM International Conference on Multimedia},
	year = {2014},
	month = {November},
	publisher = {ACM},
	type = {Conference},
	abstract = {The proposed demo shows how our system automatically zooms and pans into tracked objects in panorama videos. At the conference site, we will set up a two-camera version of the system, generating live panorama videos, where the system zooms and pans tracking people using colored hats. Additionally, using a stored soccer game video from a five 2K camera setup at Alfheim stadium in Tromso from the European league game between Troms{\o} IL and Tottenham Hotspurs, the system automatically follows the ball.},
	keywords = {Conference},
	author = {Vamsidhar Reddy {Gaddam} and Langseth, Ragnar and H{\r a}kon Kvale {Stensland} and Griwodz, Carsten and Halvorsen, P{\r a}l}
}
@inproceedings {Gaddam2014a,
	title = {Automatic Real-Time Zooming and Panning on Salient Objects from a Panoramic Video},
	journal = {Proceedings of the ACM International Conference on Multimedia - MM {\textquoteright}14},
	year = {2014},
	pages = {725{\textendash}726},
	publisher = {ACM Press},
	address = {New York, New York, USA},
	isbn = {9781450330633},
	doi = {10.1145/2647868.2654882},
	url = {http://dl.acm.org/citation.cfm?doid=2647868.2654882},
	author = {Vamsidhar Reddy {Gaddam} and Langseth, Ragnar and H{\r a}kon Kvale {Stensland} and Griwodz, Carsten and Halvorsen, P{\r a}l and Landsverk, {\O}ystein}
}
@article {stensland-bagadus,
	title = {Bagadus: an Integrated Real-Time System for Soccer Analytics},
	journal = {ACM Transactions on Multimedia Computing, Communications, and Applications},
	volume = {10},
	number = {1s},
	year = {2014},
	month = {January},
	pages = {14:1-14:21},
	abstract = {The importance of winning has increased the role of performance analysis in the sports industry, and this underscores how statistics and technology keep changing the way sports are played. Thus, this is a growing area of interest, both from a computer system view in managing the technical challenges and from a sport performance view in aiding the development of athletes. In this respect, Bagadus is a real-time prototype of a sports analytics application using soccer as a case study. Bagadus integrates a sensor system, a soccer analytics annotations system, and a video processing system using a video camera array. A prototype is currently installed at Alfheim Stadium in Norway, and in this article, we describe how the system can be used in real-time to playback events. The system supports both stitched panorama video and camera switching modes and creates video summaries based on queries to the sensor system. Moreover, we evaluate the system from a systems point of view, benchmarking different approaches, algorithms, and trade-offs, and show how the system runs in real time.},
	doi = {10.1145/2541011},
	author = {H{\r a}kon Kvale {Stensland} and Vamsidhar Reddy {Gaddam} and Tenn{\o}e, Marius and Espen O. {Helgedagsrud} and N{\ae}ss, Mikkel and Henrik Kjus {Alstad} and Mortensen, Asgeir and Langseth, Ragnar and Lj{\o}dal, Sigurd and Landsverk, {\O}ystein and Griwodz, Carsten and Halvorsen, P{\r a}l and Stenhaug, Magnus and Johansen, Dag}
}
@article {19145,
	title = {Bagadus: An integrated real-time system for soccer analytics},
	journal = {ACM Transactions on Multimedia Computing, Communications, and Applications},
	volume = {10},
	year = {2014},
	pages = {1{\textendash}21},
	publisher = {ACM},
	issn = {15516857},
	doi = {10.1145/2541011},
	url = {http://dl.acm.org/citation.cfm?doid=2576908.2541011},
	author = {H{\r a}kon Kvale {Stensland} and Landsverk, {\O}ystein and Griwodz, Carsten and Halvorsen, P{\r a}l and Vamsidhar Reddy {Gaddam} and Tenn{\o}e, Marius and Helgedagsrud, Espen and N{\ae}ss, Mikkel and Henrik Kjus {Alstad} and Mortensen, Asgeir and Langseth, Ragnar and Lj{\o}dal, Sigurd}
}
@inproceedings {Gaddam2014b,
	title = {Be your own cameraman: real-time support for zooming and panning into stored and live panoramic video},
	journal = {Proceedings of the 5th ACM Multimedia Systems Conference on - MMSys {\textquoteright}14},
	year = {2014},
	pages = {168{\textendash}171},
	publisher = {ACM Press},
	address = {New York, New York, USA},
	isbn = {9781450327053},
	doi = {10.1145/2557642.2579370},
	url = {http://dl.acm.org/citation.cfm?doid=2557642.2579370},
	author = {Vamsidhar Reddy {Gaddam} and Langseth, Ragnar and H{\r a}kon Kvale {Stensland} and Gurdjos, Pierre and Charvillat, Vincent and Griwodz, Carsten and Halvorsen, P{\r a}l}
}
@inproceedings {mmsys.2014-02-12.5304482962,
	title = {Be Your Own Cameraman: Real-Time Support for Zooming and Panning Into Stored and Live Panoramic Video},
	journal = {Proceedings of the 5th annual ACM conference on Multimedia Systems (MMSYS)},
	year = {2014},
	month = {March},
	publisher = {ACM},
	type = {Conference},
	abstract = {High-resolution panoramic video with a wide field-of-view is popular in many contexts. However, in many examples, like surveillance and sports, it is often desirable to zoom and pan into the generated video. A challenge in this respect is real-time support, but in this demo, we present an end-to-end real-time panorama system with interactive zoom and panning. Our system installed at Alfheim stadium, a Norwegian premier league soccer team, generates a cylindrical panorama from five 2K cameras live where the perspective is corrected in real-time when presented to the client. This gives a better and more natural zoom compared to existing systems using perspective panoramas and zoom operations using plain crop. Our experimental results indicate that virtual views can be generated far below the frame-rate threshold, i.e., on a GPU, the processing requirement per frame is about 10\~milliseconds. The proposed demo lets participants interactively zoom and pan into stored panorama videos generated at Alfheim stadium and from a live 2-camera array on-site.},
	doi = {10.1145/2557642.2579370},
	author = {Vamsidhar Reddy {Gaddam} and Langseth, Ragnar and H{\r a}kon Kvale {Stensland} and Gurdjos, Pierre and Charvillat, Vincent and Griwodz, Carsten and Johansen, Dag and Halvorsen, P{\r a}l}
}
@article {19144,
	title = {A correction to Andersson's fusion tree construction},
	journal = {Theoretical Computer Science},
	volume = {520},
	year = {2014},
	pages = {130{\textendash}132},
	publisher = {Elsevier},
	issn = {03043975},
	doi = {10.1016/j.tcs.2013.09.028},
	url = {http://linkinghub.elsevier.com/retrieve/pii/S0304397513007202},
	author = {Halvorsen, P{\r a}l and Griwodz, Carsten}
}
@inproceedings {sport.2014-ism-bayer,
	title = {An Evaluation of Debayering Algorithms on GPU for Real-Time Panoramic Video Recording},
	journal = {IEEE International Symposium on Multimedia (ISM 2014)},
	year = {2014},
	publisher = {IEEE},
	type = {Conference},
	abstract = {Modern video cameras normally only capture a single color per pixel, commonly arranged in a Bayer pattern. This means that we must restore the missing color channels in the image or the video frame in post-processing, a process referred to as debayering. In a live video scenario, this operation must be performed efficiently in order to output each frame in real-time, while also yielding acceptable visual quality. Here, we evaluate debayering algorithms implemented on a GPU for real-time panoramic video recordings using multiple 2K-resolution cameras.},
	author = {Langseth, Ragnar and Vamsidhar Reddy {Gaddam} and H{\r a}kon Kvale {Stensland} and Griwodz, Carsten and Halvorsen, P{\r a}l}
}
@inproceedings {2660509,
	title = {Event Understanding in Endoscopic Surgery Videos},
	journal = {HuEvent {\textquoteright}14: Proceedings of the 1st ACM International Workshop on Human Centered Event Understanding from Multimedia},
	year = {2014},
	pages = {17{\textendash}22},
	publisher = {ACM},
	address = {New York, NY, USA},
	isbn = {978-1-4503-3120-3},
	doi = {http://doi.acm.org/10.1145/2660505.2660509},
	author = {Guggenberger, Mario and Riegler, Michael and Lux, Mathias and Halvorsen, P{\r a}l}
}
@inproceedings {Simula.simula.2538,
	title = {Interactive Zoom and Panning From Live Panoramic Video},
	journal = {Proceeding of the 24th ACM Workshop on Network and Operating Systems Support for Digital Audio and Video (NOSSDAV)},
	year = {2014},
	publisher = {ACM},
	type = {Workshop},
	address = {New York, NY, USA},
	abstract = {Panorama video is becoming increasingly popular, and we present an end-to-end real-time system to interactively zoom and pan into high-resolution panoramic videos. Compared to existing systems using perspective panoramas with cropping, our approach creates a cylindrical panorama. Here, the perspective is corrected in real-time, and the result is a better and more natural zoom. Our experimental results also indicate that such zoomed virtual views can be generated far below the frame-rate threshold. Taking into account recent trends in device development, our approach should be able to scale to a large number of concurrent users in the near future.},
	keywords = {Workshop},
	author = {Vamsidhar Reddy {Gaddam} and Langseth, Ragnar and Lj{\o}dal, Sigurd and Gurdjos, Pierre and Charvillat, Vincent and Griwodz, Carsten and Halvorsen, P{\r a}l}
}
@inproceedings {Gaddam:2014:IZP:2597176.2578264,
	title = {Interactive Zoom and Panning from Live Panoramic Video},
	journal = {Proceedings of Network and Operating System Support on Digital Audio and Video Workshop},
	year = {2014},
	pages = {19:19{\textendash}{\textendash}19:24},
	publisher = {ACM},
	address = {New York, NY, USA},
	keywords = {panning, panorama video, real-time, zoom},
	isbn = {978-1-4503-2706-0},
	doi = {10.1145/2578260.2578264},
	url = {http://doi.acm.org/10.1145/2578260.2578264},
	author = {Vamsidhar Reddy {Gaddam} and Langseth, Ragnar and Lj{\o}dal, Sigurd and Gurdjos, Pierre and Charvillat, Vincent and Griwodz, Carsten and Halvorsen, P{\r a}l}
}
@misc {gtc2014,
	title = {Performance and Application of the NVIDIA NVENC H.264 Encoder},
	howpublished = {GPU Technology Conference 2014},
	year = {2014},
	month = {03/2014},
	publisher = {Nvidia},
	abstract = {This poster describes the delivery pipeline in the Bagadus soccer analysis system. The delivery pipeline takes a real-time stitched panorama video, and generates a personal virtual camera that can be controlled by the clients (end-users). An important component in this pipeline is the H.264 encoding of the personalized virtual view before delivery. By using Nvidia{\textquoteright}s NVENC hardware encoder, we are able to maintain the same visual quality as the software x264 encoder with a reduction in both CPU utilization and encode latency.},
	url = {http://on-demand.gputechconf.com/gtc/2014/poster/pdf/P4188_real-time_panorama_video_NVENC.pdf},
	author = {Martin Alexander {Wilhelmsen} and H{\r a}kon Kvale {Stensland} and Vamsidhar Reddy {Gaddam} and Halvorsen, P{\r a}l and Griwodz, Carsten}
}
@article {stensland-ijsc,
	title = {Processing Panorama Video in Real-Time},
	journal = {International Journal of Semantic Computing},
	volume = {8},
	number = {2},
	year = {2014},
	month = {September},
	pages = {209-227},
	abstract = {There are many scenarios where high resolution, wide field of view video is useful. Such panorama video may be generated using camera arrays where the feeds from multiple cameras pointing at different parts of the captured area are stitched together. However, processing the different steps of a panorama video pipeline in real-time is challenging due to the high data rates and the stringent timeliness requirements. In our research, we use panorama video in a sport analysis system called Bagadus. This system is deployed at Alfheim stadium in Troms{\o}, and due to live usage, the video events must be generated in real-time. In this paper, we describe our real-time panorama system built using a low-cost CCD HD video camera array. We describe how we have implemented different components and evaluated alternatives. The performance results from experiments ran on commodity hardware with and without co-processors like graphics processing units (GPUs) show that the entire pipeline is able to run in real-time.},
	doi = {10.1142/S1793351X14400054},
	author = {H{\r a}kon Kvale {Stensland} and Vamsidhar Reddy {Gaddam} and Tenn{\o}e, Marius and Espen O. {Helgedagsrud} and N{\ae}ss, Mikkel and Henrik Kjus {Alstad} and Griwodz, Carsten and Halvorsen, P{\r a}l and Johansen, Dag}
}
@article {19153,
	title = {Processing Panorama Video in Real-time},
	journal = {International Journal of Semantic Computing},
	volume = {08},
	year = {2014},
	pages = {209{\textendash}227},
	publisher = {World Scientific},
	issn = {1793-351X},
	doi = {10.1142/S1793351X14400054},
	url = {http://www.worldscientific.com/doi/abs/10.1142/S1793351X14400054},
	author = {H{\r a}kon Kvale {Stensland} and Vamsidhar Reddy {Gaddam} and Tenn{\o}e, Marius and Helgedagsrud, Espen and N{\ae}ss, Mikkel and Henrik Kjus {Alstad} and Griwodz, Carsten and Halvorsen, P{\r a}l}
}
@inproceedings {Kellerer2014a,
	title = {Real-Time HDR Panorama Video},
	journal = {Proceedings of the ACM International Conference on Multimedia - MM {\textquoteright}14},
	year = {2014},
	pages = {1205{\textendash}1208},
	publisher = {ACM Press},
	address = {New York, New York, USA},
	isbn = {9781450330633},
	doi = {10.1145/2647868.2655049},
	url = {http://dl.acm.org/citation.cfm?doid=2647868.2655049},
	author = {Kellerer, Lorenz and Vamsidhar Reddy {Gaddam} and Langseth, Ragnar and H{\r a}kon Kvale {Stensland} and Griwodz, Carsten and Halvorsen, P{\r a}l}
}
@inproceedings {acmmm2014hdrshort,
	title = {Real-Time HDR Panorama Video},
	journal = {ACM International Conference on Multimedia},
	year = {2014},
	month = {November},
	type = {Conference},
	abstract = {The interest for wide field of view panorama video is increasing. In this respect, we have an application that uses an array of cameras that overlook a soccer stadium. The input of these cameras are stitched together to provide a panoramic view of the stadium. One of the challenges we face is that large parts of the field are obscured by shadows on sunny days. Such circumstances cause unsatisfying video quality. We have therefore implemented and evaluated multiple algorithms related to high dynamic range (HDR) video. The evaluation shows that a combination of several approaches gives the most useful results in our scenario.},
	keywords = {Conference},
	author = {Kellerer, Lorenz and Vamsidhar Reddy {Gaddam} and Langseth, Ragnar and H{\r a}kon Kvale {Stensland} and Griwodz, Carsten and Johansen, Dag and Halvorsen, P{\r a}l}
}
@inproceedings {mmsys.2014-02-18.0527842670,
	title = {Soccer Video and Player Position Dataset},
	journal = {Proceedings of the 5th annual ACM conference on Multimedia Systems (MMSYS)},
	year = {2014},
	publisher = {ACM},
	type = {Conference},
	abstract = {This paper presents a dataset of body-sensor traces and corresponding videos from several professional soccer games captured in late 2013 at the Alfheim Stadium in Troms{\o}, Norway.Player data, including field position, heading, and speed are sampled at 20 Hz using the highly accurate ZXY Sport Tracking system. Additional per-player statistics, like total distance covered and distance covered in different speed classes, are also included with a 1 Hz sampling rate. The provided videos are in high-definition and captured using two stationary camera arrays positioned at an elevated position above the tribune area close to the center of the field. The camera array is configured to cover the entire soccer field, and each camera can be used individually or as a stitched panorama video. This combination of body-sensor data and videos enables computer-vision algorithms for feature extraction, object tracking, background subtraction, and similar, to be tested against the ground truth contained in the sensor traces.},
	author = {Svein Arne {Pettersen} and Johansen, Dag and Johansen, H{\r a}vard and Berg-Johansen, Vegard and Vamsidhar Reddy {Gaddam} and Mortensen, Asgeir and Langseth, Ragnar and Griwodz, Carsten and H{\r a}kon Kvale {Stensland} and Halvorsen, P{\r a}l}
}
@inproceedings {Pettersen2014a,
	title = {Soccer Video and Player Position Dataset},
	journal = {Proceedings of the 5th ACM Multimedia Systems Conference on - MMSys {\textquoteright}14},
	year = {2014},
	pages = {18{\textendash}23},
	publisher = {ACM Press},
	address = {New York, New York, USA},
	abstract = {Abstract This paper presents a dataset of body-sensor traces and corresponding videos from several professional soccer games captured in late 2013 at the Alfheim Stadium in Troms{\o}, Norway. Player data, including field position , heading, and speed are sampled at 20Hz ... $\backslash$n},
	isbn = {9781450327053},
	doi = {10.1145/2557642.2563677},
	url = {http://dl.acm.org/citation.cfm?doid=2557642.2563677},
	author = {Svein Arne {Pettersen} and Halvorsen, P{\r a}l and Johansen, H{\r a}vard and Berg-Johansen, Vegard and Vamsidhar Reddy {Gaddam} and Mortensen, Asgeir and Langseth, Ragnar and Griwodz, Carsten and H{\r a}kon Kvale {Stensland}}
}
@inproceedings {Simula.simula.2656,
	title = {Study the Effects of Camera Misalignment on 3D Measurements for Efficient Design of Vision-Based Inspection Systems},
	journal = {8th Hellenic Conference on Artificial Intelligence (SETN 2014)},
	year = {2014},
	month = {Mary},
	publisher = {Springer-Verlag},
	type = {Annual},
	abstract = {Vision based inspection systems for 3D measurements using single camera, are extensively used in several industries, today. Due to transportation and/or servicing of these systems, the camera in this system is prone to mis-alignment from its original position. In such situations, although a high quality calibration exists, the accuracy of 3D measurement is affected. In this paper, we propose a statistical tool or methodology which involves. a) Studying the significance of the effects of 3d measurements errors due to camera mis-alignment. b) Modelling the error data using regression models. c) Deducing expressions to determine tolerances of camera mis-alignment for an acceptable inaccuracy of the system. This tool can be used by any 3D measuring system using single camera. Resulting tolerances can be directly used for mechanical design of camera placement in the vision based inspection systems.},
	keywords = {Workshop},
	author = {Dwarakanath, Deepak and Griwodz, Carsten and Halvorsen, P{\r a}l and Lildballe, Jacob},
	editor = {Likas, Aristidis and Blekas, Konstantinos and Kalles, Dimitris}
}
@inbook {19152,
	title = {Study the Effects of Camera Misalignment on 3D Measurements for Efficient Design of Vision-Based Inspection Systems},
	booktitle = {Artificial Intelligence: Methods and Applications},
	series = {Lecture Notes in Computer Science},
	volume = {8445},
	year = {2014},
	pages = {150{\textendash}163},
	publisher = {Springer},
	organization = {Springer},
	address = {N/A},
	keywords = {Camera calibration, Camera misalignment and Regression models, Vision based inspection systems},
	isbn = {978-3-319-07063-6},
	doi = {10.1007/978-3-319-07064-3\_13},
	url = {http://dx.doi.org/10.1007/978-3-319-07064-3\_13},
	author = {Dwarakanath, Deepak and Griwodz, Carsten and Halvorsen, P{\r a}l and Lildballe, Jacob},
	editor = {Blekas, Konstantinos and Likas, Aristidis and Kalles, Dimitris}
}
@inproceedings {sport.2014-ism-short-nvenc,
	title = {Using a Commodity Hardware Video Encoder for Interactive Video Streaming},
	journal = {IEEE International Symposium on Multimedia (ISM 2014)},
	year = {2014},
	publisher = {IEEE},
	type = {Conference},
	abstract = {Over the last years, video streaming has become one of the most dominant Internet services. A trend now is that due to the increased availability of high-speed internet access, multimedia services are becoming more interactive and immersive. Examples of such applications are both cloud gaming and systems where users can interact with high-resolution content. Over the last few years, hardware video encoders have been built into commodity hardware. We evaluate one of these encoders in a scenario where we have individual streams delivered to the end users. Our results show that we can reduce almost half of the CPU time spent on video processing, while also greatly reducing the power consumption on the system. We also compare the visual video quality and the frame size of the hardware based encoder, and we find no significant difference compared to a software based approach.},
	author = {Martin Alexander {Wilhelmsen} and H{\r a}kon Kvale {Stensland} and Vamsidhar Reddy {Gaddam} and Mortensen, Asgeir and Langseth, Ragnar and Griwodz, Carsten and Halvorsen, P{\r a}l}
}
@inproceedings {19165,
	title = {Work Like a Bee -Taking Advantage of Diligent Crowdsourcing Workers},
	journal = {MediaEval 2014 Workshop, Barcelona, Catalunya, Spain},
	year = {2014},
	month = {10/2014},
	publisher = {CEUR Workshop Proceedings},
	address = {Barcelona, Catalonia/Spain},
	author = {Riegler, Michael and Preben N. {Olsen} and Halvorsen, P{\r a}l}
}
@inproceedings {Simula.simula.2050,
	title = {Analysis of a Real-World HTTP Segment Streaming Case},
	journal = {Proceedings of the European Interactive TV Conference (EuroITV 2013)},
	year = {2013},
	month = {June},
	pages = {75-84},
	publisher = {ACM},
	type = {Conference},
	abstract = {Today, adaptive HTTP segment streaming is a popular way to deliver video content to users. The benefits of HTTP segment streaming include its scalability, high performance and easy deployment, especially the possibility to reuse the already deployed HTTP infrastructure. However, current research focuses merely on client side statistics like for example achieved video qualities and adaption algorithms. To quantify the properties of such streaming systems from a service provider point of view, we have analyzed both sender and receiver side logging data provided by a popular Norwegian streaming provider. For example, we observe that more than 90\% of live streaming clients send their requests for the same video segment with an inter-arrival time of only 10 seconds. Moreover, the logs indicate that the server sends substantially less data than is actually reported to be received by the clients, and the origin server streams data to less clients than there really are. Based on these facts, we conclude that HTTP segment streaming really makes use of the HTTP cache infrastructure without the need to change anything in the parts of Internet that are not controlled by the streaming provider.},
	author = {Kupka, Tomas and Griwodz, Carsten and Halvorsen, P{\r a}l and Johansen, Dag and Hovden, Torgeir},
	editor = {George Lekakos Pa {Cremonesi}}
}
@inproceedings {mmsys.2013-03-15.9787518415,
	title = {Bagadus: an Integrated System for Arena Sports Analytics - a Soccer Case Study -},
	journal = {Proceedings of the 4th annual ACM conference on Multimedia Systems (MMSYS)},
	year = {2013},
	month = {March},
	pages = {48-59},
	publisher = {ACM},
	type = {Conference},
	abstract = {Sports analytics is a growing area of interest, both from a computer system view to manage the technical challenges and from a sport performance view to aid the development of athletes. In this paper, we present Bagadus, a prototype of a sports analytics application using soccer as a case study. Bagadus integrates a sensor system, a soccer analytics annotations system and a video processing system using a video camera array. A prototype is currently installed at Alfheim Stadium in Norway, and in this paper, we describe how the system can follow and zoom in on particular player(s). Next, the system will playout events from the games using stitched panorama video or camera switching mode and create video summaries based on queries to the sensor system. Further- more, we evaluate the system from a systems point of view, benchmarking different approaches, algorithms and trade-offs.},
	isbn = {978-1-4503-1894-5},
	author = {Halvorsen, P{\r a}l and S{\ae}grov, Simen and Mortensen, Asgeir and David Kai Christ {Kristensen} and Eichhorn, Alexander and Stenhaug, Magnus and Dahl, Stian and H{\r a}kon Kvale {Stensland} and Vamsidhar Reddy {Gaddam} and Griwodz, Carsten and Johansen, Dag},
	editor = {Zimmermann, Roger}
}
@inproceedings {Simula.simula.2052,
	title = {Cache-Centric Video Recommendation: an Approach to Improve the Efficiency of YouTube Caches},
	journal = {Proceedings of the International Conference on Multimedia Systems (MMSys)},
	year = {2013},
	month = {March},
	pages = {261-270},
	publisher = {ACM},
	type = {Conference},
	abstract = {In this paper, we take advantage of the user behavior of re- questing videos from the related list provided by YouTube and the user behavior of requesting videos from the top of this related list to improve the performance of YouTube{\textquoteright}s caches. We recommend a related list reordering approach which modifies the order of the videos shown on the related list based on the content in the cache. The main goal of our reordering approach is to push the contents already in the cache to the top of the related list and push non-cached contents towards the bottom, which increases the likelihood that the already cached content will be chosen by the viewer. We analyze the benefits of our approach by an investigation that is based on two traces collected from an university campus. Our analysis shows that the proposed reordering approach for related list would lead to a 2 to 5 times increase in cache hit rate compared to an approach without reordering the related list. The increase in hit rate would lead to a 5.12\% to 18.19\% reduction in server load or back-end bandwidth usage. This increase in hit rate and reduction in back-end bandwidth reduces the latency in streaming the video requested by the viewer and has the potential to improve the overall performance of YouTube{\textquoteright}s content distribution system. An analysis of YouTube{\textquoteright}s recommendation system reveals that related lists are created from a small pool of videos, which increases the potential for caching content from related lists and reordering based on the content in the cache.},
	keywords = {Conference},
	author = {Dilip Kumar {Krishnappa} and Zink, Michael and Griwodz, Carsten and Halvorsen, P{\r a}l},
	editor = {Griwodz, Carsten}
}
@inproceedings {Simula.simula.2150,
	title = {Combining Video and Player Telemetry for Evidence-Based Decisions in Soccer},
	journal = {Proceedings of the International Congress on Sports Science Research and Technology Support (icSPORTS)},
	year = {2013},
	month = {September},
	type = {Conference},
	abstract = {Technology is changing how soccer clubs train and interact with their supporters. Systems that provide acquisition and visualization of low-level player telemetry, like distance covered and speed, are already being widely adopted. A key observation is that such data when correlated with actual in-game video footage is a powerful tool for evidence-based decisions. As data volume and complexity grow, efficient tools for auto- mated high-precision retrieval become essential. This paper describes the unique combination of a radio-based sensor platform and several custom video retrieval systems in operational use at Troms{\o} Idrettslag (TIL), a Norwegian premier league soccer club. The systems have been developed using an experimental computer- science method where several prototypes were built and deployed for evaluation in close collaboration with the intended users. Although our method of computer-system prototyping has not yielded commercial quality products, it has enabled us to construct several novel systems combining low-level player telemetry with video retrieval, annotations, and user-centric security.},
	author = {Johansen, H{\r a}vard and Svein Arne {Pettersen} and Halvorsen, P{\r a}l and Johansen, Dag},
	editor = {Jo{\~a}o Barreiros {Correia}}
}
@inproceedings {Simula.simula.2054,
	title = {Commute Path Bandwidth Traces From 3G Networks: Analysis and Applications},
	journal = {Proceedings of the International Conference on Multimedia Systems (MMSys)},
	year = {2013},
	month = {March},
	publisher = {ACM},
	type = {Conference},
	abstract = {In this dataset paper, we present and make available real- world measurements of the throughput that was achieved at the application layer when adaptive HTTP streaming was performed over 3G networks using mobile devices. For the streaming sessions, we used popular commute routes in and around Oslo (Norway) traveling with different types of public transportation (metro, tram, train, bus and ferry). We also have a few logs using a car. Each log provides a times- tamp, GPS coordinates and the measured number of bytes downloaded for approximately every second of the route. The dataset can be used in several ways, but the most obvious application is to emulate the same network bandwidth behavior (on specific geographical positions) for repeated experiments.},
	keywords = {Conference},
	author = {Riiser, Haakon and Vigmostad, Paul and Griwodz, Carsten and Halvorsen, P{\r a}l},
	editor = {Griwodz, Carsten}
}
@inproceedings {ism.2013-11-29.3515257247,
	title = {Efficient Implementation and Processing of a Real-Time Panorama Video Pipeline},
	journal = {IEEE International Symposium on Multimedia (ISM 2013)},
	year = {2013},
	pages = {76-83},
	publisher = {IEEE},
	type = {Conference},
	abstract = {High resolution, wide field of view video generated from multiple camera feeds has many use cases. However, processing the different steps of a panorama video pipeline in real-time is challenging due to the high data rates and the stringent requirements of timeliness. We use panorama video in a sport analysis system where video events must be generated in real-time. In this respect, we present a system for real-time panorama video generation from an array of low-cost CCD HD video cameras. We describe how we have implemented different components and evaluated alternatives. We also present performance results with and without co- processors like graphics processing units (GPUs), and we evaluate each individual component and show how the entire pipeline is able to run in real-time on commodity hardware.},
	keywords = {Conference},
	author = {Tenn{\o}e, Marius and Espen O. {Helgedagsrud} and N{\ae}ss, Mikkel and Henrik Kjus {Alstad} and H{\r a}kon Kvale {Stensland} and Vamsidhar Reddy {Gaddam} and Johansen, Dag and Griwodz, Carsten and Halvorsen, P{\r a}l}
}
@book {Simula.simula.2048,
	title = {Proceeding of the 23rd ACM Workshop on Network and Operating Systems Support for Digital Audio and Video (NOSSDAV{\textquoteright}13)},
	year = {2013},
	month = {February},
	publisher = {ACM},
	abstract = {It is a pleasure to welcome you to the 23rd ACM Workshop on Network and Operating Systems Support for Digital Audio and Video (NOSSDAV) in Oslo, Norway. For years, NOSSDAV has been recognized as a unique venue that attracts researchers and practitioners working on operating systems and networking support for emerging multimedia applications and services. This year{\textquoteright}s workshop tries to continue the long tradition and aims at accommodating timely exchange of research results and fostering lively, constructive discussions on potentially controversial concepts and solutions in the area of systems support for multimedia.},
	keywords = {Conference},
	isbn = {978-1-4503-1892-1},
	author = {B{\"o}sz{\"o}rm{\'e}nyi, Laszlo and Halvorsen, P{\r a}l}
}
@misc {Simula.simula.1930,
	title = {Real-time Panorama Video Processing Using NVIDIA GPUs},
	howpublished = {GPU Tecnology Conference 2013},
	year = {2013},
	month = {03/2013},
	publisher = {Nvidia},
	abstract = {Sports analytics is a growing area of interest, both from a computer system view to manage the technical challenges and from a sport performance view to aid the development of athletes. We have been working on Bagadus, a prototype of a sports analytics application using soccer as a case study. Bagadus integrates a sensor system, a soccer analytics annotationssystem and a video processing system using a video camera array. A prototype is currently installed at Alfheim Stadium in Norway. An important part of the system is playback of events from the games using stitched panorama video. This results in a lot of technical challenges to keep the creation of these panorama videos in real time. To be able to do this, we utilize the power of GPGPU by use of NVIDIA GPUs and CUDA.Link to the 2013 GPU Technology Conference poster program: http://www.gputechconf.com/page/posters.html\#vidimg},
	url = {http://on-demand.gputechconf.com/gtc/2013/poster/pdf/P0201_MariusTennoe.pdf},
	author = {Tenn{\o}e, Marius and Espen O. {Helgedagsrud} and N{\ae}ss, Mikkel and Henrik Kjus {Alstad} and H{\r a}kon Kvale {Stensland} and Halvorsen, P{\r a}l and Griwodz, Carsten}
}
@inproceedings {Simula.simula.2094,
	title = {Is Today{\textquoteright}s Public Cloud Suited to Deploy Hardcore Realtime Services?},
	journal = {LNCS - Lecture Notes in Computer Science},
	year = {2013},
	publisher = {Euro-Par LSDVE 2013},
	type = {Workshop},
	abstract = {{\textquotedblright}Cloud computing{\textquotedblright} is a popular way for application providers to obtain a flexible server and network infrastructure. Providers deploying applications with tight response time requirements such as games, are reluctant to use clouds. An important reason is the lack of real-time guarantees. This paper evaluates the actual, practical soft real-time CPU performance of current cloud services, with a special focus on online games. To perform this evaluation, we created a small benchmark and calibrated it to take a few milliseconds to run (often referred to as a microbenchmark). Repeating this benchmark at a high frequency gives an overview of available resources over time. From the experimental results, we find that public cloud services deliver performance mostly within the requirements of popular online games, where Microsoft Azure Virtual machines give a significantly more stable performance than Amazon EC2.},
	author = {Raaen, Kjetil and Petlund, Andreas and Halvorsen, P{\r a}l}
}
@inproceedings {Simula.simula.1650,
	title = {BAGADUS: an Integrated System for Soccer Analysis},
	journal = {Proceedings of the International Conference on Distributed Smart Cameras (ICDSC)},
	year = {2012},
	month = {October/November},
	publisher = {ACM/IEEE},
	type = {Conference},
	abstract = {In this demo, we present Bagadus, a prototype of a soccer analysis application which integrates a sensor system, soccer analytics annotations and video processing of a video camera array. The prototype is currently installed at Alfheim Stadium in Norway, and we demonstrate how the system can follow and zoom in on particular player(s), and playout events from the games using the stitched panorama video and/or the camera switching mode.},
	author = {Simen, S{\ae}grow and Eichhorn, Alexander and Emerslund, J{\o}rgen and H{\r a}kon Kvale {Stensland} and Griwodz, Carsten and Halvorsen, P{\r a}l}
}
@inproceedings {Simula.simula.1652,
	title = {A Comparison of Quality Scheduling in Commercial Adaptive HTTP Streaming Solutions on a 3G Network},
	journal = {Proceeding of the ACM Workshop on Mobile Video (MoVid)},
	year = {2012},
	month = {February},
	pages = {25-30},
	publisher = {ACM},
	type = {Workshop},
	abstract = {There are many available commercial streaming solutions that perform quality adaption. An important issue with respect to users\&$\#$39; perceived quality is how the system schedules the quality levels to match the available network resources. In this study, we compare several adaptive media players on the market to see how they perform in challenging streaming scenarios on a mobile 3G network. Bandwidth data collected in real-world field trials is used in all tests. We investigate how the media players respond to fluctuating bandwidth and outages, and how this affects the quality levels used, the bandwidth utilization, and the number and duration of buffer underruns. We found significant differences in performance and optimization goals between the different players\&$\#$39; schedulers. We conclude that the quality scheduler is an important factor in providing a satisfying quality of experience when using an adaptive media player.},
	author = {Riiser, Haakon and Bergsaker, H{\r a}kon and Vigmostad, Paul and Halvorsen, P{\r a}l and Griwodz, Carsten}
}
@inproceedings {Simula.simula.1644,
	title = {Evaluating Performance of Feature Extraction Methods for Practical 3D Imaging Systems},
	journal = {27th International Conference Image and Vision Computing New Zealand},
	year = {2012},
	month = {December},
	publisher = {ACM - International Conference Proceedings Series (ICPS)},
	type = {Conference},
	abstract = {Smart cameras are extensively used for multi-view capture and 3D rendering applications. To achieve high quality, such applications are required to estimate accurate position and orientation of the cameras (called as camera calibration-pose estimation). Traditional techniques that use checkerboard or special markers, are impractical in larger spaces. Hence, feature-based calibration (auto-calibration), is necessary. Such calibration methods are carried out based on features extracted and matched between stereo pairs or multiple cameras. Well known feature extraction methods such as SIFT (Scale Invariant Feature Transform), SURF (Speeded-Up Robust Features) and ORB (Oriented FAST and Rotated BRIEF) have been used for auto-calibration. The accuracy of auto-calibration is sensitive to the accuracy of features extracted and matched between a stereo pair or multiple cameras. In practical imaging systems, we encounter several issues such as blur, lens distortion and thermal noise that affect the accuracy of feature detectors. In our study, we investigate the behaviour of SIFT, SURF and ORB through simulations of practical issues and evaluate their performance targeting 3D reconstruction (based on epipolar geometry of a stereo pair). Our experiments are carried out on two real-world stereo image datasets of various resolutions. Our experimental results show significant performance differences between feature extractors\&$\#$39; performance in terms of accuracy, execution time and robustness to blur, lens distortion and thermal noise of various levels. Eventually, our study identifies suitable operating ranges that helps other researchers and developers of practical imaging solutions.},
	keywords = {Conference},
	author = {Dwarakanath, Deepak and Eichhorn, Alexander and Halvorsen, P{\r a}l and Griwodz, Carsten}
}
@inproceedings {drefereedinproceedingsreference.2012-12-10.5290080794,
	title = {Faster and More Accurate Feature-Based Calibration for Widely Spaced Camera Pairs},
	journal = {Digital Information and Communication Technology and it{\textquoteright}s Applications (DICTAP)},
	year = {2012},
	month = {May},
	pages = {87-92},
	publisher = {IEEE},
	type = {Conference},
	abstract = {The increasing demand for live multimedia systems in gaming, art and entertainment industries, has resulted in the development of multiview capturing systems that use camera arrays. We investigate sparse (widely spaced) camera arrays to capture scenes of large volume space. A vital aspect of such systems is camera calibration, which provides an understanding of the scene geometry used for 3D reconstruction. Traditional algorithms make use of a calibration object or identifiable markers placed in the scene, but this is impractical and inconvenient for large spaces. Hence, we take the approach of features-based calibration. Existing schemes based on SIFT (Scale Invariant Feature Transform), exhibit lower accuracy than marker-based schemes due to false positives in feature matching, variations in baseline (spatial displacement between the camera pair) and changes in viewing angle. Therefore, we propose a new method of SIFT feature based calibration, which adopts a new technique for the detection and removal of wrong SIFT matches and the selection of an optimal subset of matches. Experimental tests show that our proposed algorithm achieves higher accuracy and faster execution for larger baselines of up to \approx2 meters, for an object distance of \approx4.6 meters, and thereby enhances the usability and scalability of multi-camera capturing systems for large spaces.},
	keywords = {Conference},
	author = {Dwarakanath, Deepak and Eichhorn, Alexander and Griwodz, Carsten and Halvorsen, P{\r a}l and Dwarakanath, Deepak}
}
@inproceedings {srmpds-lears,
	title = {LEARS: a Lockless, Relaxed-Atomicity State Model for Parallel Execution of a Game Server Partition},
	journal = {The 41st International Conference on Parallel Processing Workshops},
	year = {2012},
	note = {Published as part of the SRMPDS workshop proceedings},
	publisher = {IACC},
	type = {Workshop},
	abstract = {Supporting thousands of interacting players in a virtual world poses huge challenges with respect to processing. Existing work that addresses the challenge utilizes a variety of spatial partitioning algorithms to distribute the load. If, however, a large number of players needs to interact tightly across an area of the game world, spatial partitioning cannot subdivide this area without incurring massive communication costs, latency or inconsistency. It is a major challenge of game engines to scale such areas to the largest number of players possible; in a deviation from earlier thinking, parallelism on multi-core architectures is applied to increase scalability. In this paper, we evaluate the design and implementation of our game server architecture, called LEARS, which allows for lock-free parallel processing of a single spatial partition by considering every game cycle an atomic tick. Our prototype is evaluated using traces from live game sessions where we measure the server response time for all objects that need timely updates. We also measure how the response time for the multi-threaded implementation varies with the number of threads used. Our results show that the challenge of scaling up a game-server can be an embarrassingly parallel problem.},
	isbn = {978-0-7695-4795-4},
	doi = {10.1109/ICPPW.2012.55},
	author = {Raaen, Kjetil and Espeland, H{\r a}vard and H{\r a}kon Kvale {Stensland} and Petlund, Andreas and Halvorsen, P{\r a}l and Griwodz, Carsten},
	editor = {Balaji, Pavan and Lin, Heshan}
}
@inproceedings {srmpds12-lls,
	title = {Low-Level Scheduling Implications for Data-Intensive Cyclic Workloads on Modern Microarchitectures},
	journal = {The 41st International Conference on Parallel Processing Workshops},
	year = {2012},
	publisher = {IACC},
	type = {Workshop},
	abstract = {Processing data intensive multimedia workloads is challenging, and scheduling and resource management are vitally important for the best possible utilization of machine resources. In earlier work, we have used work-stealing, which is frequently used today, and proposed improvements. We found already then that no singular work-stealing variant is ideally suited for all workloads. Therefore, we investigate in more detail in this paper how workloads consisting of various multimedia filter sequences should be scheduled on a variety of modern processor architectures to maximize performance. Our results show that a low-level scheduler additionally cannot achieve optimal performance without taking the specific micro-architecture, the placement of dependent tasks and cache sizes into account. These details are not generally available for application developers and they differ between deployments. Our proposal is therefore to use performance monitoring and dynamic adaption for the cyclic workloads of our target multimedia scenario, where operations are repeated cyclically on a stream of data.},
	isbn = {978-0-7695-4795-4},
	doi = {10.1109/ICPPW.2012.49},
	author = {Espeland, H{\r a}vard and Preben N. {Olsen} and Halvorsen, P{\r a}l and Griwodz, Carsten},
	editor = {Balaji, Pavan and Lin, Heshan}
}
@inproceedings {Simula.simula.1162,
	title = {Network Traffic From Anarchy Online: Analysis, Statistics and Applications},
	journal = {Proceedings of the 2012 Multimedia Systems Conference},
	year = {2012},
	month = {February},
	publisher = {The Association for Computing Machinery},
	type = {Conference},
	abstract = {We present a dataset - a real-world, server-side packet trace - from Anarchy Online. Anarchy Online is a science fiction-themed massively multiplayer online roleplaying game (MMORPG), published and developed by Funcom. We present statistics from the network traffic and show that it is a representative dataset for similar games. From the dataset, one can extract several key characteristics from such scenarios like payload sizes, packet rates, data delivery latencies, retransmission statistics, loss rates and stream correlation. The dataset can be used several ways: by replaying the game traffic, components like congestion control mechanisms, middlewares, packet schedulers, router queue behaviour, etc. can be analysed. Based on the observed statistics from the trace, such interactive game traffic shows completely different behaviour compared to the greedy, high-rate streams most network mechanisms are designed for, e.g., file download, video streaming and web-surfing. We hope that the dataset can be used to push research forward in the field of system support for games.},
	isbn = {978-1-4503-1131-1},
	author = {Petlund, Andreas and Halvorsen, P{\r a}l and P{\r a}l Frogner {Hansen} and Lindgren, Torbj{\"o}rn and Casais, Rui},
	editor = {Claypool, Mark}
}
@inproceedings {Simula.simula.1658,
	title = {Performance of On-Off Traffic Stemming From Live Adaptive Segmented HTTP Video Streaming},
	journal = {Proceedings of the IEEE Conference on Local Computer Networks (LCN)},
	year = {2012},
	pages = {405-413},
	publisher = {IEEE},
	type = {Conference},
	abstract = {Nowadays, several live and on-demand streaming solutions use HTTP for signaling and data delivery. A frequently used technique is to chop a continuous stream into segments, encode these in multiple qualities and make these available for download using plain HTTP methods. This approach has become known as dynamic adaptive segment streaming over HTTP. Its advantage is that the deployed web infrastructure is easily reused, even for live segment streaming. In this case, however, it is not strictly bulk traffic. We show in this paper, that the streaming source is essentially an on-off source. Furthermore, this paper analyzes several client-controlled segment request strategies for live adaptive HTTP segment streaming. We present experimental results showing the benefits and drawbacks of each strategy with respect to achieved video quality, smoothness of playback and end-to-end delay. We show that it matters how clients request segments. The results indicate strongly that synchronization of client requests has a negative impact on router queues and leads to increased packet loss, and should thus be avoided to achieve a high goodput.},
	keywords = {Conference},
	doi = {10.1109/LCN.2012.6423654},
	author = {Kupka, Tomas and Halvorsen, P{\r a}l and Griwodz, Carsten}
}
@article {espeland-vp8,
	title = {Reducing Processing Demands for Multi-Rate Video Encoding: Implementation and Evaluation},
	journal = {International Journal of Multimedia Data Engineering and Management},
	volume = {3},
	number = {2},
	year = {2012},
	pages = {1-19},
	abstract = {Segmented adaptive HTTP streaming has become the de facto standard for video delivery over the Internet for its ability to scale video quality to the available network resources. Here, each video is encoded in multiple qualities, i.e., running the expensive encoding process for each quality layer. However, these operations consume both a lot of time and resources, and in this paper, the authors propose a system for reusing redundant steps in a video encoder to improve the multi-layer encoding pipeline. The idea is to have multiple outputs for each of the target bitrates and qualities where the intermediate processing steps share and reuse the computational heavy analysis. A prototype has been implemented using the VP8 reference encoder, and their experimental results show that for both low- and high-resolution videos the proposed method can significantly reduce the processing demands and time when encoding the different quality layers.},
	doi = {10.4018/jmdem.2012040101},
	author = {Espeland, H{\r a}vard and H{\r a}kon Kvale {Stensland} and Dag Haavi {Finstad} and Halvorsen, P{\r a}l}
}
@inproceedings {Simula.simula.798,
	title = {Bitrate and Video Quality Planning for Mobile Streaming Scenarios Using a GPS-Based Bandwidth Lookup Service},
	journal = {Proceedings of the IEEE International Conference on Multimedia and Expo (ICME)},
	year = {2011},
	month = {July},
	pages = {1-6},
	publisher = {IEEE},
	type = {Conference},
	abstract = {One of the main challenges when streaming video to mo- bile devices is to handle fluctuating bandwidth and frequent network outages as the device is brought in and out of areas with network coverage. In this paper, we propose bitrate and video quality planning algorithms for mobile streaming scenarios using a GPS-based bandwidth-lookup service in order to reduce frequently changing video quality and the number of playout interruptions. Our real world experiments using an adaptive segmented HTTP video streaming system while travelling on popular commute routes indicate that the users{\textquoteright} quality of experience is greatly increased.},
	isbn = {978-1-61284-348-3},
	doi = {ICME.2011.6012045},
	author = {Riiser, Haakon and Vigmostad, Paul and Griwodz, Carsten and Halvorsen, P{\r a}l}
}
@inproceedings {Simula.simula.700,
	title = {Demo: Quality-Adaptive Video Streaming With Dynamic Bandwidth Aggregation on Roaming, Multi-Homed Clients},
	journal = {Proceedings of the 9th international conference on Mobile systems, applications, and services (MOBISYS)},
	year = {2011},
	month = {July},
	pages = {355-356},
	publisher = {ACM},
	type = {Conference},
	address = {New York},
	abstract = {In this paper, we combined our earlier work in quality adaptive streaming and bandwidth aggregation with automatic network detection. If a client detects and can connect to multiple networks, the bandwidth is aggregated dynamically, resulting in a higher video quality.},
	isbn = {978-1-4503-0643-0},
	author = {Evensen, Kristian and Petlund, Andreas and Kaspar, Dominik and Griwodz, Carsten and Halvorsen, P{\r a}l and Riiser, Haakon and Vigmostad, Paul},
	editor = {Agrawala, Ashok}
}
@inproceedings {Simula.simula.752,
	title = {A Demonstration of a Lockless, Relaxed Atomicity State Parallel Game Server (LEARS)},
	journal = {Workshop on Network and Systems Support for Games (NetGames 2011)},
	year = {2011},
	pages = {1-3},
	publisher = {IEEE / ACM},
	type = {Workshop},
	abstract = {Games where thousands of players can interact concurrently pose many challenges with regards to the massive parallelism. Earlier work within the field suggests that this is difficult due to synchronization issues. In this paper, we present an implementation of a game server architecture based on a model that allows for massive parallelism. The system is evaluated using traces from live game sessions that has been scaled up to generate massive workloads. We measure the differences in server response time for all objects that need timely updates. We also measure how the response time for the multithreaded implementation varies with the number of threads used. Our results show that the case of implementing a game-server can actually be highly parallel problem.},
	isbn = {978-1-4577-1932-5},
	author = {Raaen, Kjetil and Espeland, H{\r a}vard and H{\r a}kon Kvale {Stensland} and Petlund, Andreas and Halvorsen, P{\r a}l and Griwodz, Carsten},
	editor = {Shirmohammadi, Shervin}
}
@misc {Simula.simula.668,
	title = {Distributed Real-Time Processing of Multimedia Data With the P2G Framework},
	year = {2011},
	month = {April},
	abstract = {P2G is a framework designed to integrate concepts from modern batch processing frameworks into the world of real-time multimedia processing, where we seek to scale transparently with the available resources. P2G consists of a compiler and run-time that analyzes dependencies dynamically and merges or splits kernel instances based on resouce availability and performance monitoring.},
	author = {Beskow, Paul and Espeland, H{\r a}vard and H{\r a}kon Kvale {Stensland} and Preben N. {Olsen} and St{\r a}le B. {Kristoffersen} and Espen Angell {Kristiansen} and Griwodz, Carsten and Halvorsen, P{\r a}l}
}
@inproceedings {Simula.simula.758,
	title = {An Evaluation of Live Adaptive HTTP Segment Streaming Request Strategies},
	journal = {Proceedings of the IEEE Conference on Local Computer Networks (LCN)},
	year = {2011},
	month = {October},
	pages = {608-616},
	publisher = {IEEE},
	type = {Conference},
	abstract = {Nowadays, several live and on-demand streaming solutions use HTTP for signaling and data delivery. A frequently used technique is to chop a continuous stream into segments, encode these in multiple qualities and make these available for download using plain HTTP methods. This approach has become known as dynamic adaptive segment streaming over HTTP. Its advantage is that the deployed web infrastructure is easily reused, even for live segment streaming. In this case, however, it is not strictly bulk traffic. We show in this paper, that the streaming source is essentially an on-off source. Furthermore, this paper analyzes several client-controlled segment request strategies for live adaptive HTTP segment streaming. We present experimental results showing the benefits and drawbacks of each strategy with respect to achieved video quality, smoothness of playback and end-to-end delay. We show that it matters how clients request segments. The results indicate strongly that synchronization of client requests has a negative impact on router queues and leads to increased packet loss, and should thus be avoided to achieve a high goodput.},
	isbn = {978-1-61284-927-0},
	author = {Kupka, Tomas and Griwodz, Carsten and Halvorsen, P{\r a}l},
	editor = {Anura Jayasumana {Pfeifer}}
}
@inproceedings {Simula.simula.802,
	title = {Flicker Effects in Adaptive Video Streaming to Handheld Devices},
	journal = {Proceedings of the ACM International Multimedia Conference (ACM MM)},
	year = {2011},
	month = {Nov/Dec},
	pages = {463-472},
	publisher = {ACM},
	type = {Conference},
	abstract = {Streaming video over the Internet requires mechanisms that limit the streams{\textquoteright} bandwidth consumption within its fair share. TCP streaming guarantees this and provides lossless streaming as a side-effect. Adaptation by packet drop does not occur in the network, and excessive startup latency and stalling must be prevented by adapting the bandwidth consumption of the video itself. However, when the adaptation is performed during an ongoing session, it may influence the perceived quality of the entire video and result in improved or reduced visual quality of experience. We have in- vestigated visual artifacts that are caused by adaptive layer switching - we call them flicker effects - and present our results for handheld devices in this paper. We considered three types of flicker, namely noise, blur and motion flicker. The perceptual impact of flicker is explored through subjective assessments. We vary both the intensity of quality changes (amplitude) and the number of quality changes per second (frequency). Users{\textquoteright} ability to detect and their acceptance of variations in the amplitudes and frequencies of the quality changes are explored across four content types. Our results indicate that multiple fac- tors influence the acceptance of different quality variations. Amplitude plays the dominant role in delivering satisfactory video quality, while frequency can also be adjusted to relieve the annoyance of flicker artifacts.},
	author = {Ni, Pengpeng and Eg, Ragnhild and Eichhorn, Alexander and Griwodz, Carsten and Halvorsen, P{\r a}l},
	editor = {Sundaram, Hari and Feng, Wu-chi and Sebe, Nicu}
}
@inproceedings {Simula.simula.750,
	title = {Improved Multi-Rate Video Encoding},
	journal = {International Symposium on Multimedia},
	year = {2011},
	pages = {293-300},
	publisher = {IEEE},
	type = {Conference},
	abstract = {Adaptive HTTP streaming is frequently used for both live and on-Demand video delivery over the Internet. Adaptiveness is often achieved by encoding the video stream in multiple qualities (and thus bitrates), and then transparently switching between the qualities according to the bandwidth fluctuations and the amount of resources available for decoding the video content on the end device. For this kind of video delivery over the Internet, H.264 is currently the most used codec, but VP8 is an emerging open-source codec expected to compete with H.264 in the streaming scenario. The challenge is that, when encoding video for adaptive video streaming, both VP8 and H.264 run once for each quality layer, i.e., consuming both time and resources, especially important in a live video delivery scenario. In this paper, we address the resource consumption issues by proposing a method for reusing redundant steps in a video encoder, emitting multiple outputs with varying bitrates and qualities. It shares and reuses the computational heavy analysis step, notably macro-block mode decision, intra prediction and inter prediction between the instances, and outputs video in several rates. The method has been implemented in the VP8 reference encoder, and experimental results show that we can encode the different quality layers at the same rates and qualities compared to the VP8 reference encoder, while reducing the encoding time significantly.},
	isbn = {978-0-7695-4589-9},
	author = {Dag Haavi {Finstad} and H{\r a}kon Kvale {Stensland} and Espeland, H{\r a}vard and Halvorsen, P{\r a}l},
	editor = {Anthony Y.H. {Liao}}
}
@inproceedings {Simula.simula.178,
	title = {Improving the Performance of Quality-Adaptive Video Streaming Over Multiple Heterogeneous Access Networks},
	journal = {Proceedings of the second annual ACM conference on Multimedia systems (MMSYS)},
	year = {2011},
	month = {February},
	pages = {57-68},
	publisher = {ACM},
	type = {Conference},
	abstract = {Devices capable of connecting to multiple, overlapping networks simultaneously are becoming increasingly common. For example, most laptops are equipped with LAN- and WLAN-interfaces, and smart phones can typically connect to both WLANs and 3G mobile networks. At the same time, streaming high-quality video is becoming increasingly popular. However, due to bandwidth limitations or the unreliable and unpredictable nature of some types of networks, streaming video can be subject to frequent periods of rebuffering and characterised by a low picture quality. In this paper, we present a client-side request scheduler that distributes requests for the video over multiple heterogeneous interfaces simultaneously. Each video is divided into independent segments with constant duration, enabling segments to be requested over separate links, utilizing all the available bandwidth. To increase performance even further, the segments are divided into smaller subsegments, and the sizes are dynamically calculated on the fly, based on the throughput of the different links. This is an improvement over our earlier subsegment approach, which divided segments into fixed size subsegments. Both subsegment approaches were evaluated with on-demand streaming and quasi-live streaming. The new subsegment approach reduces the number of playback interruptions and improves video quality significantly for all cases where the earlier approach struggled. Otherwise, they show similar performance.},
	isbn = {978-1-4503-0518-1},
	author = {Evensen, Kristian and Kaspar, Dominik and Griwodz, Carsten and Halvorsen, P{\r a}l and Audun Fosselie {Hansen} and Paal Einar {Engelstad}},
	editor = {Ketan Mayer-Pate {Begen}}
}
@inproceedings {Simula.simula.662,
	title = {Mobile Video Streaming Using Location-Based Network Prediction and Transparent Handover},
	journal = {NOSSDAV},
	year = {2011},
	month = {May},
	pages = {21-26},
	publisher = {ACM},
	type = {Conference},
	edition = {21},
	address = {New York},
	abstract = {A well known challenge with mobile video streaming is fluctuating bandwidth. As the client devices move in and out of network coverage areas, the users may experience varying signal strengths, competition for the available resources and periods of network outage. These conditions have a significant effect on video quality. In this paper, we present a video streaming solution for roaming clients that is able to compensate for the effects of oscillating bandwidth through bandwidth prediction and video quality scheduling. We combine our existing adaptive segmented HTTP streaming system with 1) an application layer framework for creating transparent multi-link applications, and 2) a location based QoS information system containing GPS coordinates and accompanying bandwidth measurements, populated through crowd-sourcing. Additionally, we use real-time traffic information to improve the prediction by, for example, estimating the length of a commute route. To evaluate our prototype, we performed real-world experiments using a popular tram route in Oslo, Norway. The client connected to multiple networks, and the results show that our solution increases the perceived video quality significantly. Also, we used simulations to evaluate the potential of aggregating bandwidth along the route.},
	isbn = {978-1-4503-0777-2},
	author = {Evensen, Kristian and Petlund, Andreas and Riiser, Haakon and Vigmostad, Paul and Kaspar, Dominik and Griwodz, Carsten and Halvorsen, P{\r a}l},
	editor = {Krasic, Charles and Li, Kang}
}
@inproceedings {Simula.simula.686,
	title = {P2G: a Framework for Distributed Real-Time Processing of Multimedia Data},
	journal = {Proceedings of the International Workshop on Scheduling and Resource Management for Parallel and Distributed Systems (SRMPDS) - The 2011 International Conference on Parallel Processing Workshops},
	year = {2011},
	month = {September},
	pages = {416-426},
	publisher = {IEEE},
	type = {Workshop},
	abstract = {The computational demands of multimedia data processing are steadily increasing as consumers call for progressively more complex and intelligent multimedia services. New multi-core hardware architectures provide the required resources, but writing parallel, distributed applications remains a labor-intensive task compared to their sequential counter-part. For this reason, Google and Microsoft implemented their respective processing frameworks MapReduce, as they allow the developer to think sequentially, yet benefit from parallel and distributed execution. An inherent limitation in the design of these processing frameworks is their inability to express arbitrarily complex workloads. The dependency graphs of the frameworks are often limited to directed acyclic graphs, or even pre-determined stages. This is particularly problematic for video encoding and other algorithms that depend on iterative execution. With the Nornir runtime system for parallel programs, which is a Kahn Process Network implementation, we addressed and solved several of these limitations. However, it is more difficult to use than other frameworks due to its complex programming model. In this paper, we build on the knowledge gained from Nornir and present a new framework, called , designed specifically for developing and processing distributed real-time multimedia data. P2G supports arbitrarily complex dependency graphs with cycles, branches and deadlines, and provides both data- and task-parallelism. The framework is implemented to scale transparently with available (heterogeneous) resources, a concept familiar from the cloud computing paradigm. We have implemented an (interchangeable) P2G to ease development. In this paper, we present a proof of concept implementation of a P2G execution node and some experimental examples using complex workloads like Motion JPEG and K-means clustering. The results show that the P2G system is a feasible approach to multimedia processing.},
	isbn = {978-0-7695-4511-0},
	author = {Espeland, H{\r a}vard and Beskow, Paul and H{\r a}kon Kvale {Stensland} and Preben N. {Olsen} and St{\r a}le B. {Kristoffersen} and Griwodz, Carsten and Halvorsen, P{\r a}l},
	editor = {Sheu, Jang-Ping and Wang, Cho-Li}
}
@inproceedings {Simula.simula.748,
	title = {Processing of Multimedia Data Using the P2G Framework},
	journal = {Proceedings of the 19th ACM international conference on Multimedia},
	year = {2011},
	pages = {819-820},
	publisher = {ACM},
	type = {Conference},
	abstract = {In this demo, we present the P2G framework designed for processing distributed real-time multimedia data. P2G supports arbitrarily complex dependency graphs with cycles, branches and deadlines. P2G is implemented to scale transparently with available resources, i.e., a concept familiar from the cloud computing paradigm. Additionally, P2G supports heterogeneous computing resources, such as x86 and GPU processing cores. We have implemented an interchangeable P2G kernel language which is meant to expose fundamental concepts of the P2G programming model and ease the application development. Here, we demonstrate the P2G execution node using a MJPEG encoder as an example workload when dynamically adding and removing processing cores.},
	isbn = {978-1-4503-0616-4},
	author = {Beskow, Paul and H{\r a}kon Kvale {Stensland} and Espeland, H{\r a}vard and Espen Angell {Kristiansen} and Preben N. {Olsen} and St{\r a}le B. {Kristoffersen} and Griwodz, Carsten and Halvorsen, P{\r a}l},
	editor = {Sundaram, Hari and Feng, Wu-chi and Sebe, Nicu}
}
@article {Simula.simula.708,
	title = {Search-Based Composition, Streaming and Playback of Video Archive Content},
	journal = {Multimedia Tools and Applications},
	number = {online first},
	year = {2011},
	abstract = {Locating content in existing video archives is both a time and bandwidth consuming process since users might have to download and manually watch large portions of superfluous videos. In this paper, we present two novel prototypes using an Internet based video composition and streaming system with a keyword-based search interface that collects, converts, analyses, indexes, and ranks video content. At user requests, the system can automatically sequence out portions of single videos or aggregate content from multiple videos to produce a single, personalized video stream on-the-fly.},
	doi = {10.1007/ s11042-011-0847-5},
	author = {Johansen, Dag and Halvorsen, P{\r a}l and Johansen, H{\r a}vard and Riiser, Haakon and Gurrin, Cathal and Olstad, Bj{\o}rn and Griwodz, Carsten and Kvalnes, {\r A}ge and Hurley, Joseph and Kupka, Tomas}
}
@inproceedings {Simula.simula.800,
	title = {Spatial Flicker Effect in Video Scaling},
	journal = {Proceedings of the International Workshop on Quality of Multimedia Experience (QoMEX)},
	year = {2011},
	month = {July},
	pages = {55-60},
	publisher = {IEEE},
	type = {Workshop},
	abstract = {Scalable video streaming may result in flicker effects - visual artifacts in video presentation due to adaptive layer switching. In our work, we have identified three types of flicker, noise, blur and motion flicker. Here, we investigate the blur and noise flicker, which are both related to the spatial domain. The perceptual impact of blur and noise flicker is explored through subjective assessments, focusing on acceptance of variations in the amplitudes and frequencies of the quality changes, across four content types. Our results indicate that the perception and acceptance of different layer variations are jointly influenced by multiple factors. When video scaling is required, frequency can be adjusted to relieve the annoyance of flicker artifacts, while amplitude still plays the dominant role in delivering satisfactory video quality. In addi- tion, contents with complex details are more affected by blur flicker than other contents. This difference is not observed for noise flicker.},
	isbn = {978-1-4577-1333-0},
	author = {Ni, Pengpeng and Eg, Ragnhild and Eichhorn, Alexander and Griwodz, Carsten and Halvorsen, P{\r a}l},
	editor = {Cristobal, Gabriel and Jacobs, An and Raake, Alexander}
}
@article {Simula.simula.860,
	title = {Using Bandwidth Aggregation to Improve the Performance of Quality-Adaptive Streaming},
	journal = {Signal Processing: Image Communication},
	volume = {27},
	number = {4},
	year = {2011},
	pages = {312-328},
	publisher = {Elsevier},
	abstract = {Devices capable of connecting to multiple, overlapping networks simultaneously is becoming increasingly common. For example, most laptops are equipped with LAN- and WLAN-interface, and smart phones can typically connect to both WLANs and 3G mobile networks. At the same time, streaming high-quality video is becoming increasingly popular. However, due to bandwidth limitations or the unreliable and unpredictable nature of some types of networks, streaming video can be subject to frequent periods of rebuffering and characterized by a low picture quality. In this paper, we present a multilink extension to the data retrieval part of the DAVVI adaptive, segmented video streaming system. DAVVI implements the same core functionality as the MPEG DASH standard. It uses HTTP to retrieve data, segments video, provides clients with a description of the content, and allows clients to switch quality during playback. Any DAVVI-data retrieval extensions can also be implemented in a DASH-solution. The multilink-enabled DAVVI client divides video segments into smaller subsegments, which are requested over multiple interfaces simultaneously. The size of each subsegment is dynamic and calculated on the fly, based on the throughput of the different links. This is an improvement over our earlier subsegment approach, which divided segments into fixed size subsegments. The quality of the video is adapted based on the measured, aggregated throughput. Both the static and the dynamic subsegment approaches were evaluated with on-demand streaming and quasi-live streaming. The new subsegment approach reduces the number of playback interruptions and improves video quality significantly for all cases where the earlier approach struggled. Otherwise, they show similar performance.},
	doi = {doi:10.1016/j.image.2011.10.007},
	author = {Evensen, Kristian and Kaspar, Dominik and Griwodz, Carsten and Halvorsen, P{\r a}l and Audun Fosselie {Hansen} and Paal Einar {Engelstad}}
}
@inproceedings {Simula.simula.690,
	title = {Using Multiple Links to Increase the Performance of Bandwidth-Intensive UDP-Based Applications},
	journal = {Proceedings of IEEE ISCC 2011},
	volume = {16},
	year = {2011},
	month = {June},
	pages = {1117-1122},
	publisher = {IEEE},
	type = {Conference},
	abstract = {Networked devices often come equipped with multiple network interfaces, and bandwidth aggregation is one of the many possible benefits of using multiple interfaces simultaneously. Real-world networks introduce several challenges that have often been ignored by related work on bandwidth aggregation. The challenges include limited connectivity due to NAT-boxes, link heterogeneity and link variability. In this paper, we present a transparent solution for proxy-based bandwidth aggregation that is able to overcome the different deployment and link heterogeneity challenges present in real-world networks. Our focus has been on increasing the performance of bandwidth-intensive UDP-based applications, and through evaluation we show that our solution efficiently aggregates bandwidth and increases the in-order throughput. Previously, we introduced a multi-link UDP proxy solution that improves in-order throughput. This paper presents a significant extension and improvement in terms of support for middle-boxes (NAT), congestion control, a client-based resequencer and support for all operating systems.},
	isbn = {978-1-4577-0678-3},
	author = {Evensen, Kristian and Kaspar, Dominik and Audun Fosselie {Hansen} and Griwodz, Carsten and Halvorsen, P{\r a}l},
	editor = {Adel S. {Elmaghraby} and Douligeris, Christos}
}
@article {Simula.simula.724,
	title = {Video Streaming Using a Location-Based Bandwidth-Lookup Service for Bitrate Planning},
	journal = {ACM Transactions on Multimedia Computing, Communications and Applications},
	volume = {8},
	number = {3},
	year = {2011},
	note = {ACCEPTED FEBRUARY 2011},
	abstract = {A lot of people around the world commute using public transportation and would like to spend this time viewing streamed video content such as news or sports updates. However, mobile wireless networks typically suffer from severe bandwidth fluctuations, and the networks are often completely unresponsive for several seconds, sometimes minutes. Today, there are several ways of adapting the video bitrate and thus the video quality to such fluctuations, e.g., using scalable video codecs or segmented adaptive HTTP streaming that switches between non-scalable video streams encoded in different bitrates. Still, for a better long-term video playout experience that avoids disruptions and frequent quality changes while using existing video adaptation technology, it is desirable to perform bandwidth prediction and planned quality adaptation. This paper describes a video streaming system for receivers equipped with a GPS. A receiver{\textquoteright}s download rate is constantly monitored, and periodically reported back to a central database along with associated GPS positional data. Thus, based on the current location, a streaming device can use a GPS-based bandwidth-lookup service in order to better predict the near-future bandwidth availability and create a schedule for the video playout that takes likely future availability into account. To create a prototype and perform initial tests, we conducted several field trials while commuting using public transportation. We show how our database has been used to predict bandwidth fluctuations and network outages, and how this information helps maintain uninterrupted playback with less compromise on video quality than possible without prediction.},
	author = {Riiser, Haakon and Endestad, Tore and Vigmostad, Paul and Griwodz, Carsten and Halvorsen, P{\r a}l}
}
@inproceedings {Simula.simula.26,
	title = {Cheat Detection Processing: a GPU Versus CPU Comparison},
	journal = {Workshop on Network and Systems Support for Games (NetGames 2010)},
	year = {2010},
	pages = {8:1-8:6},
	publisher = {ACM IEEE},
	type = {Conference},
	abstract = {In modern online multi-player games, game providers are struggling to keep up with the many different types of cheating. Cheat detection is a task that requires a lot of computational resources. Advances made within the field of heterogeneous computing architectures, such as graphics processing units (GPUs), have given developers easier access to considerably more computational resources, enabling a new approach to solving this issue. In this paper, we have developed a small game simulator that includes a customizable physics engine and a cheat detection mechanism that checks the physical model used by the game. To make sure that the mechanisms are fair to all players, they are executed on the server side of the game system. We investigate the advantages of implementing physics cheat detection mechanisms on a GPU using the Nvidia CUDA framework, and we compare the GPU implementation of the cheat detection mechanism with a CPU implementation. The results obtained from the simulations show that offloading the cheat detection mechanisms to the GPU reduces the time spent on cheat detection, enabling the servers to support a larger number of clients.},
	isbn = {978-1-4244-8355-6},
	author = {H{\r a}kon Kvale {Stensland} and Myrseth, Martin and Griwodz, Carsten and Halvorsen, P{\r a}l},
	editor = {Cheok, Adrian and Huang, Jiung-Yao and Ishibashi, Yutaka}
}
@inproceedings {Simula.mpg.22,
	title = {Composing Personalized Video Playouts Using Search},
	journal = {Proceedings of the International Workshop on Visual Content Identification and Search (VCIDS) - ICME workshops},
	year = {2010},
	month = {July},
	pages = {1534-1539},
	publisher = {IEEE},
	type = {Workshop},
	abstract = {We conjecture that composition of video events from various sources into personalized video playouts will become an important part of next generation streaming systems. Here, video search is a key component since it enables users to retrieve candidate video events based on their interests. One of the main challenges, however, is to analyze the videos in order to correctly identify the various events used to annotate and index the video data. Key problems with current video analysis solutions include that they 1) are complex and therefore require a lot of processing time resulting in large delays; 2) that they can only identify a limited set of events; and 3) that they are still too inaccurate, both giving false positives and failing to find all events. In our DAVVI prototype, we therefore extract metadata for our video search engine by combining existing automatic video analysis tools with currently untapped textual information available in the Internet. This provides an end-user experience where textual query results can be combined dynamically into seamless, highly personalized video playouts using an adaptive torrent-like HTTP streaming solution.},
	isbn = {978-1-4244-7491-2},
	author = {Johansen, Dag and Johansen, H{\r a}vard and Halvorsen, P{\r a}l and Olstad, Bj{\o}rn and Gurrin, Cathal and Griwodz, Carsten},
	editor = {Lu, Jian and Hua, Xian-Sheng and China Dong {Xu}}
}
@inproceedings {Simula.ND.379,
	title = {Enhancing Video-on-Demand Playout Over Multiple Heterogeneous Access Networks},
	journal = {Consumer Communications and Networking Conference (CCNC)},
	year = {2010},
	publisher = {IEEE},
	type = {Conference},
	abstract = {Multimedia streaming is increasing in popularity and has become one of the dominating services on the Internet today. Even though user devices are often equipped with multiple network interfaces and in reach of several access networks at the same time, media streams are normally communicated over only one of the available Internet connections. In this paper, we explore the challenges and potential benefits of using multiple access networks simultaneously. Exploiting HTTP{\textquoteright}s capability of handling requests for specific byte ranges of a file, we present the implementation of a lightweight, application-layer, on-demand streaming service that requires no changes to existing servers and infrastructure. Based on real-world experiments with a multihomed host, we investigate the potential performance gains of video-on-demand playout. We achieve a bandwidth aggregation efficiency of 90\% when downloading over 3 heterogeneous access networks in parallel. In addition, we analyze the effect of file segmentation on the buffer requirements and the startup latency.},
	isbn = {978-1-4244-5176-0},
	author = {Kaspar, Dominik and Evensen, Kristian and Paal Einar {Engelstad} and Audun Fosselie {Hansen} and Halvorsen, P{\r a}l and Griwodz, Carsten},
	editor = {IEEE, }
}
@article {Simula.mpg.6,
	title = {Frequent Layer Switching for Perceived Quality Improvements of Coarse-Grained Scalable Video},
	journal = {ACM Multimedia Systems Journal},
	volume = {16},
	number = {3},
	year = {2010},
	month = {May},
	pages = {171-182},
	abstract = {Scalable video is an attractive option for adapting the bandwidth consumption of streaming video to the available bandwidth. Fine-grained scalability can adapt most closely to the available bandwidth, but this comes at the cost of a higher overhead compared to more coarse- grained videos. In the context of VoD streaming, we have therefore explored whether a similar adaptation to the available bandwidth can be achieved by performing layer switching in coarse-grained scalable videos. In this approach, enhancement layers of a video stream are swit- ched on and off to achieve any desired longer term band- width. We have performed three user studies, two using mobile devices and one using an HDTV display, to eval- uate the idea. In several cases, the far-from-obvious con- clusion is that layer switching is a viable way of achieving bit-rate savings and fine-grained bit-rate adaptation even for rather short times between layer switches, but it does, however, depend on scaling dimensions, content and dis- play device.},
	author = {Ni, Pengpeng and Eichhorn, Alexander and Griwodz, Carsten and Halvorsen, P{\r a}l}
}
@misc {Simula.mpg.38,
	title = {Latency Can Kill - Defeat the Lag!},
	howpublished = {The Gathering World \& Pegasus},
	year = {2010},
	month = {April},
	abstract = {"Lagger" er et vanlig uttrykk blant spillere p{\r a} Internett - en betegnelse som uttrykker stor forsinkelse som sterkt p{\r a}virker spillopplevelsen. Forskjellige spill har forskjellige krav for at spillopplevelsen skal bli god. For eksempel, i first-person-shooter (FPS) spill som Call of Duty vil forsinkelser over 100 ms redusere spillbarheten. I multiplayer rollespill (MMOGs) som World of Warcraft og Anarchy Online kan man tolerere opp til 500 ms.},
	author = {Petlund, Andreas and Halvorsen, P{\r a}l and Griwodz, Carsten}
}
@inproceedings {Simula.mpg.20,
	title = {Low Overhead Container Format for Adaptive Streaming},
	journal = {Proceedings of the ACM Multimedia Systems (MMSys)},
	year = {2010},
	month = {February},
	pages = {193-198},
	publisher = {ACM},
	type = {Conference},
	abstract = {Current segmented HTTP streaming systems provide scal- able and quality adaptive video delivery services to a huge number of users. However, while they support a wide range of bandwidths and enable arbitrary content-based composition, their current formats have shortcomings like large overheads, live streaming delays, etc. We have therefore de- veloped an adaptive media player that works around these problems while still using standard components like H.264/AVC for video, and MP3 for audio. The system\&$\#$39;s adaptivity allows the player to pick a quality level that makes good use of available bandwidth and CPU resources while at the same time maintaining smooth uninterrupted playback, as well as offering near instant seek and startup times. This paper presents an appropriate way of coding the seg- ments and a simple multimedia container format that is optimized for adaptive streaming and video composition over HTTP. We show that our format is sufficiently advanced to contain any payload type, while being trivial to parse and translate to other container formats. Additionally, we show that our format is second to none in terms of overhead, without incurring any penalties on live streaming.},
	isbn = {978-1-60558-914-5},
	author = {Riiser, Haakon and Halvorsen, P{\r a}l and Griwodz, Carsten and Johansen, Dag},
	editor = {Mayer-Patel, Ketan and Feng, Wu-chi}
}
@inproceedings {Simula.simula.207,
	title = {Maximizing Video Quality for Several Unicast Streams in a Multipath Overlay Network},
	journal = {Proceedings of International Conference on Internet Multimedia Systems Architecture and Application (IMSAA)},
	year = {2010},
	month = {Dec},
	publisher = {IEEE},
	type = {Conference},
	abstract = {A streaming system that uses an overlay network for multipath streaming needs to make decisions concerning the distribution of the available bandwidth among all of its clients. This decision making should aim at delivering the best possible quality to all clients while providing an optimal utilization of the network resources. We consider a scenario where most requests are negligibly overlapped in time. It implies that using multicast is not efficient, and instead, the streams are striped and allocated to multiple paths from the sever to the client. To evaluate how well the rate-allocation algorithms approach optimality, we have earlier built a benchmarking system that provides the optimal solution for assigning available bandwidth to delivery paths. However, as video is not linearly related to bitrate, the trivial maximization of the total consumed bandwidth does not necessary maximize the video quality. To address this problem, we define a metric that assesses a video quality for a group of clients that we use as a utility function in the revised benchmarking system. Due to its concavity, this utility function also distributes the bandwidth resources proportionally fair between the clients of the system.},
	isbn = {978-1-4244-7931-3},
	author = {Boudko, Svetlana and Leister, Wolfgang and Griwodz, Carsten and Halvorsen, P{\r a}l},
	editor = {Sanjoy Paul Ashut {Dutta}}
}
@article {Simula.mpg.30,
	title = {The Nornir Run-Time System for Parallel Programs Using Kahn Process Networks on Multi-Core Machines - a Flexible Alternative to MapReduce},
	journal = {The Journal of Supercomputing},
	number = {Online first},
	year = {2010},
	note = {In print: January 2013, Volume 63, Issue 1, pp 191-217},
	pages = {1-27},
	abstract = {Even though shared-memory concurrency is a paradigm frequently used for developing parallel applications on small- and middle-sized machines, experience has shown that it is hard to use. This is largely caused by synchro- nization primitives which are low-level, inherently nondeterministic, and, consequently, non-intuitive to use. In this paper, we present the Nornir run-time system. Nornir is comparable to well-known frameworks such as MapReduce and Dryad that are recognized for their efficiency and simplicity. Unlike these frameworks, Nornir also supports process structures containing branches and cycles. Nornir is based on the formalism of Kahn process networks, which is a shared-nothing, message-passing model of concurrency. We deem this model a simple and deterministic alternative to shared-memory concurrency. Experiments with real and synthetic benchmarks on up to 8 CPUs show that per- formance in most cases scales almost linearly with the number of CPUs, when not limited by data dependencies. We also show that the modeling flexibility allows Nornir to outperform its MapReduce counter-parts using well-known benchmarks.},
	doi = {10.1007/s11227-010-0503-2},
	author = {Vrba, Zeljko and Halvorsen, P{\r a}l and Griwodz, Carsten and Beskow, Paul and Espeland, H{\r a}vard and Johansen, Dag}
}
@inproceedings {Simula.ND.411,
	title = {Program Obfuscation by Strong Cryptography},
	journal = {Proceedings of the International Conference on Availability, Reliability and +Security (ARES), Krakow, Poland, February 2010},
	year = {2010},
	pages = {242-247},
	publisher = {N/A},
	type = {Conference},
	abstract = {Program obfuscation is often employed by malware in order to avoid detection by anti-virus software, but it has many other legitimate uses, such as copy protection, software licensing or private computing in the cloud. In this paper, we present a program obfuscation method that is based on the combination of strong encryption of code and data and a CPU simulator (CSPIM) that implements theMIPS I instruction set. Our method is different from existing methods in that only a single word (32- bits) of the protected code or data is present as plain-text in main memory. Furthermore, our method allows the possibility of externally supplying the decryption key to the simulator. We have extensively tested the simulator, and it is able to successfully execute C programs compiled by the gcc cross-compiler. Even though purely software-based method cannot provide perfect protection, we argue that this approach significantly raises the bar for reverse-engineers, especially wen combined with existing program obfucation techniques.},
	isbn = {978-1-4244-5879-0},
	doi = {10.1109/ARES.2010.47},
	author = {Vrba, Zeljko and Halvorsen, P{\r a}l and Griwodz, Carsten}
}
@inproceedings {Simula.mpg.28,
	title = {Pull-Patching: a Combination of Multicast and Adaptive Segmented HTTP Streaming},
	journal = {Proceedings of the International Conference on Multimedia (ACM MM)},
	year = {2010},
	month = {October},
	pages = {799-802},
	publisher = {ACM},
	type = {Conference},
	abstract = {Multicast delivery for video streaming gains credibility with the introduction of commercial IPTV. We therefore revisit patching, a video-on-demand idea from the 1990s. We have built Pull-Patching, an approach that combines the patch- ing ideas with adaptive segmented HTTP streaming, a unicast technique that is used by most commercial providers of large-scale, true video-on-demand in the Internet today. The prototype is tested in a combined Internet and lab environment where we show the influence of practical factors like packet loss, delay and limited resource availability, and identify several details that require further study.},
	isbn = {978-1-60558-933-6},
	author = {Jacobsen, Espen and Griwodz, Carsten and Halvorsen, P{\r a}l},
	editor = {del Bimbo, Alberto and Chang, Shih-Fu and Arnold W. M. {Smeulders}}
}
@inproceedings {Simula.telco.2,
	title = {Quality-Adaptive Scheduling for Live Streaming Over Multiple Access Networks},
	journal = {The 20th International Workshop on Network and Operating Systems Support for Digital Audio and Video (NOSSDAV 2010)},
	year = {2010},
	month = {June},
	pages = {21-26},
	publisher = {ACM},
	type = {Conference},
	abstract = {Video streaming ranks among the most popular services offered through the Internet today. At the same time, accessing the Internet over public WiFi and 3G networks has become part of our everyday lives. However, streaming video in wireless environments is often subject to frequent periods of rebuffering and characterized by low picture quality. In particular, achieving smooth and quality-adaptive streaming of live video poses a big challenge in mobile scenarios. Building on the observation that the subjective video experience on mobile devices decreases when quality changes are more frequent than every 1 to 2 seconds, we present a client-side scheduler that retrieves segments of several video encodings over heterogeneous network interfaces simultaneously. By extending the DAVVI streaming platform with support for multihoming, the proposed scheduler{\textquoteright}s performance is experimentally evaluated. The results show that our scheduler reduces the video interruptions and achieves a higher and more stable average quality over multiple, truly heterogeneous wireless interfaces.},
	isbn = {978-1-4503-0043-8},
	author = {Evensen, Kristian and Kupka, Tomas and Kaspar, Dominik and Halvorsen, P{\r a}l and Griwodz, Carsten},
	editor = {Dick C. A. {Bulterman}}
}
@article {Simula.mpg.10,
	title = {Reducing Game Latency by Migration, Core-Selection and TCP Modifications},
	journal = {International Journal of Advanced Media and Communication (IJAMC)},
	volume = {4},
	number = {4},
	year = {2010},
	note = {Special issue on selected papers from NetGames},
	pages = {343-363},
	abstract = {Massively multi-player online games (MMOGs) have stringent latency requirements and handle large numbers of concurrent players. To support these conflicting requirements, it is common to divide the virtual environment into virtual regions, and spawn multiple instances of isolated game areas; to serve multiple distinct groups of players. As MMOGs attract players across the world, dispersing these regions and instances on geographically distributed servers is plausible. With Ginnungagap, we present the prototype implementation and evaluation of functionality for migrating objects to support dynamic re-distribution of game state; with a distributed name server efficiently maintaining references to migrated objects. Core selection algorithms, using players latencies, can then locate an optimal placement for a given region or instance. The variance of the measured latencies (and core selection algorithm) are reduced by enabling our TCP modifications for latency reduction for non-greedy streams. Correspondingly, we anticipate a decrease in aggregate latency for the affected players.},
	doi = {10.1504/IJAMC.2010.036835},
	author = {Beskow, Paul and Petlund, Andreas and Erikstad, Geir and Griwodz, Carsten and Halvorsen, P{\r a}l}
}
@inproceedings {Simula.ND.409,
	title = {A Simple Improvement of the Work-Stealing Scheduling Algorithm},
	journal = {Proceedings of the International Conference on Complex, Intelligent and Software Intensive Systems (CISIS) - International Workshop on Multi-Core Computing Systems (MuCoCoS), Krakow, Poland, February 2010},
	year = {2010},
	pages = {925-930},
	publisher = {N/A},
	type = {Workshop},
	abstract = {Work-stealing is the todays algorithm of choice for dynamic load-balancing of irregular parallel applications on multiprocessor systems. We have evaluated the algorithm\&$\#$39;s efficiency on a variety of workloads, including scatter-gather workloads, which occur in common algorithms such as MapReduce. We have discovered that work-stealing scheduling suffers serious scalability problems with fine-grained parallelism because of contention over run-queues. We therefore propose a simple modification to the work-stealing algorithm that significantly improves its performance on scatter-gather workloads, without any negative impact on other types of workloads.},
	isbn = {978-1-4244-5917-9},
	doi = {10.1109/CISIS.2010.67},
	author = {Vrba, Zeljko and Halvorsen, P{\r a}l and Griwodz, Carsten}
}
@article {Simula.mpg.24,
	title = {Support for Enterprise Consolidation of I/O Bound Services},
	journal = {Software: Practice and Experience},
	volume = {40},
	number = {10},
	year = {2010},
	pages = {1035-1051},
	abstract = {In this article, we evaluate the performance effects of I/O bound workloads on a specific virtual machine, an important component of an enterprise cloud computing infrastructure. In particular, we demonstrate that (1) the I/O workload of one guest system may adversely affect the I/O performance of another for the XEN hypervisor and (2) the general I/O performance is degraded due to various overheads. Next, we have devised a light-weight, complementary, backwards-compatible alternative to hypervisor-based virtualization techniques called Bonsai. Our software provides low-overhead I/O performance isolation by transparently applying traffic shaping to system calls in a cost-effective manner. Using this system, I/O resource consumption can be controlled at a very fine granularity. Furthermore, using video streaming experiments, where we limit the I/O bandwidth available to each service, we show that we are able to achieve the required level of resource isolation on a per process basis with only a negligible CPU overhead and without reducing the I/O performance.},
	author = {Kvalnes, {\r A}ge and Johansen, Dag and Griwodz, Carsten and Halvorsen, P{\r a}l}
}
@misc {Simula.mpg.36,
	title = {Temming Av Multikjerneprosessorer - Fordeler Og Utfordringer},
	howpublished = {The Gathering World \& Pegasus},
	year = {2010},
	month = {April},
	abstract = {De fleste datamaskiner har i dag en multikjerneprosessor. Kanskje du ogs{\r a} har et grafikkort i datamaskinen din, eller kanskje du har en Playstation 3? Da har du ogs{\r a} en asymmetrisk multikjerneprosessor - som stort sett bare utnyttes n{\r a}r du spiller spill!},
	author = {H{\r a}kon Kvale {Stensland} and Espeland, H{\r a}vard and Griwodz, Carsten and Halvorsen, P{\r a}l}
}
@inproceedings {Simula.mpg.2,
	title = {Tips, Tricks and Troubles: Optimizing for Cell and GPU},
	journal = {The 20th International Workshop on Network and Operating Systems Support for Digital Audio and Video (NOSSDAV 2010)},
	year = {2010},
	month = {June},
	pages = {75-80},
	publisher = {ACM},
	type = {Conference},
	abstract = {When used efficiently, modern multicore architectures, such as Cell and GPUs, provide the processing power required by resource demanding multimedia workloads. However, the diversity of resources exposed to the programmers, intrinsically requires specific mindsets for efficiently utilizing these resources - not only compared to an x86 architecture, but also between the Cell and the GPUs. In this context, our analysis of 14 different Motion-JPEG implementations indicates that there exists a large potential for optimizing performance, but there are also many pitfalls to avoid. By experimentally evaluating algorithmic choices, inter-core data communication (memory transfers) and architecture-specific capabilities, such as instruction sets, we present tips, tricks and troubles with respect to efficient utilization of the available resources.},
	isbn = {978-1-4503-0043-8},
	author = {H{\r a}kon Kvale {Stensland} and Espeland, H{\r a}vard and Griwodz, Carsten and Halvorsen, P{\r a}l},
	editor = {Dick C. A. {Bulterman}}
}
@inproceedings {Simula.mpg.34,
	title = {VESP: a Video-Enabled Enterprise Search Platform},
	journal = {Proceeding of the International Conference on Data and Knowledge Engineering (ICDKE)},
	year = {2010},
	publisher = {IEEE Computer Society},
	type = {Conference},
	abstract = {In this paper, we present how to provide a novel and potentially disruptive multimedia service by modifying a widely deployed commercial enterprise search engine. The idea is to transparently integrate rich multimedia data with traditional textual-oriented query results. This includes that the search engine automatically discovers and extracts relevant scenes from a large knowledge repository of existing videos and produces a new, customized video of events matching the user query. To evaluate our prototype, we have performed experiments using a data set from a knowledge repository in Microsoft consisting of PowerPoint presentations with corresponding videos. Our initial results demonstrate that such integration can be implemented efficiently, and that potential users prefer to have the opportunity to enrich the search results with corresponding video.},
	author = {Halvorsen, P{\r a}l and Johansen, Dag and Olstad, Bj{\o}rn and Kupka, Tomas and Tenn{\o}e, Sverre},
	editor = {Xiang, Yang and Samarati, Pierangela and Hu, Jiankun and Zhou, Wanlei and Sadeghi, Ahmad-Reza}
}
@inproceedings {Simula.mpg.26,
	title = {VESP: Enriching Enterprise Document Search Results With Aligned Video Summarization},
	journal = {Proceedings of the International Conference on Multimedia (ACM MM)},
	year = {2010},
	month = {October},
	pages = {1603-1604},
	publisher = {ACM},
	type = {Conference},
	abstract = {In this demo, we present a video-enabled enterprise search platform (vESP), an application prototype that enhances a widely deployed commercial enterprise search engine with video streaming. In large enterprises, there exists a lot of information in form of presentations with corresponding video. Using our enhancements, a user can select and combine slides from different presentations generating a new slide deck dynamically and the corresponding video clips are concatenated and presented vis-a-vis the slides on-the-fly. The prototype is evaluated using a data set from Microsoft, and our initial user surveys indicate that the opportunity to enrich the search results with corresponding video is embraced by potential users.},
	isbn = {978-1-60558-933-6},
	author = {Halvorsen, P{\r a}l and Johansen, Dag and Olstad, Bj{\o}rn and Kupka, Tomas and Tenn{\o}e, Sverre},
	editor = {Shih-Fu Chang Albe {del Bimbo}}
}
@article {Simula.mpg.32,
	title = {Web Services Discovery Across Heterogeneous Military Networks},
	journal = {IEEE Communications Magazine},
	volume = {48},
	number = {10},
	year = {2010},
	pages = {84-90},
	abstract = {NATO has identified web services standards as a key enabler for interoperability between the different military systems used by various NATO nations. Compared to many civilian systems, mil- itary networks vary greatly in terms of comput- ing resources, network bandwidth, mobility and stability, and distributed applications use several different networks concurrently or interact across them. In such dynamic and heterogeneous environments, runtime service discovery is a necessity. According to the W3C, {\textquotedblleft}discovery is the act of locating a machine-processable description of a Web service-related resource that may have been previously unknown and that meets certain functional criteria.{\textquotedblright} In this article we present our approach to service discovery, where we combine web services standards and proprietary solutions using our prototype inter- operability gateway. This approach has been experimentally evaluated in a military experi- ment featuring both mobile ad hoc networks and fixed infrastructure networks, and the results show that transparent discovery between propri- etary solutions and web services discovery stan- dards can be achieved.},
	author = {Frank Trethan {Johnsen} and Hafs{\o}e, Trude and Eggen, Anders and Griwodz, Carsten and Halvorsen, P{\r a}l}
}
@inproceedings {Simula.ND.307,
	title = {An Analysis of the Heterogeneity and IP Packet Reordering Over Multiple Wireless Networks},
	journal = {IEEE Symposium on Computers and Communications (ISCC)},
	number = {CFP09SCC},
	year = {2009},
	pages = {637-642},
	publisher = {IEEE},
	type = {Conference},
	abstract = {With the increasing deployment of wireless technologies, such as WLAN, HSPA, and WiMAX, it is often the case that simultaneous coverage of several access networks is available to a single user device. In addition, devices are also often equipped with multiple network interfaces. Thus, if we can exploit all available network interfaces at the same time, we can obtain advantages like the aggregation of bandwidth and increased fault tolerance. However, the heterogeneity and dynamics of the links also introduce challenges. Due to different link delays, sending packets of the same flow over multiple heterogeneous paths causes the reordering of packets. In this paper, we quantify how network heterogeneity and the use of multiple links affect IP packet reordering. We show with practical measurements, according to commonly used metrics, that packet reordering over multiple links exceeds the reordering caused by common connections in high-speed, wide-area networks. We also demonstrate the heterogeneity and reordering exceeds the assumptions presented in related work. By using sufficiently large buffers, packet reordering can be avoided. However, for devices with high resource constraints, the workload of using large buffers is expensive. Sender-side solutions of dividing and scheduling a packet sequence to available links towards the client can reduce the buffer requirements. Initial experiments with a static scheduler that has knowledge of average link delay and throughput estimates show that packet reordering can be reduced by only 38\% due to the dynamic heterogeneity of the two links.},
	isbn = {978-1-4244-4671-1},
	author = {Kaspar, Dominik and Evensen, Kristian and Audun Fosselie {Hansen} and Paal Einar {Engelstad} and Halvorsen, P{\r a}l and Griwodz, Carsten}
}
@inproceedings {Simula.ND.391,
	title = {DAVVI: a Prototype for the Next Generation Multimedia Entertainment Platform},
	journal = {ACM Multimedia Conference},
	year = {2009},
	note = {Demo paper.},
	month = {October},
	pages = {989-990},
	publisher = {ACM},
	type = {Conference},
	abstract = {In this demo, we present DAVVI, a prototype of the next generation multimedia entertainment platform. It delivers multi-quality video content in a torrent-similar way like known systems from Move Networks, Microsoft and Apple do. However, it also provides a brand new, personalized user experience. Through applied search, personalization and recommendation technologies, end-users can efficiently search and retrieve highlights and combine arbitrary events in a customized manner using drag and drop. The created playlists of video segments are then delivered back to the system to improve future search and recommendation results. Here, we demonstrate this system using \mbox{a soccer example.}},
	isbn = {978-1-60558-608-3},
	author = {Johansen, Dag and Johansen, H{\r a}vard and Aarflot, Tjalve and Hurley, Joseph and Kvalnes, {\r A}ge and Gurrin, Cathal and Sav, Sorin and Olstad, Bj{\o}rn and Aaberg, Erik and Endestad, Tore and Riiser, Haakon and Griwodz, Carsten and Halvorsen, P{\r a}l},
	editor = {Gao, Wen and Rui, Yong and Hanjalic, Alan and Xu, Changsheng and Steinbach, Eckehard and Abdulmotaleb El {Saddik} and Zhou, Michelle}
}
@inproceedings {Simula.nd.471,
	title = {Evaluating Ginnungagap: a Middleware for Migration of Partial Game-State Utilizing Core-Selection for Latency Reduction},
	journal = {Proceedings of the workshop on Network and System Support for Games (NetGames)},
	year = {2009},
	month = {November},
	pages = {1-6},
	publisher = {IEEE},
	type = {Workshop},
	abstract = {Massively multi-player online games (MMOGs) have stringent la- tency requirements and must support large numbers of concurrent players. To handle these conflicting requirements, it is common to divide the virtual environment into virtual regions, and spawn multiple instances of isolated game areas (known as dungeons or instances) to serve multiple distinct groups of players. As MMOGs attract players from all around the world, it is plausible to disperse these regions and instances on geographically distributed servers. Core selection algorithms can then be applied to locate an opti- mal server for placing a region or instance, based on player la- tencies. Functionality for migrating objects supports this objective, with a distributed name server ensuring that references to the moved objects are efficiently maintained. As a result, we anticipate a decrease in aggregate latency for the affected players. With GINNUNGAGAP we present the implementation and evaluation of a middleware that combines these ideas and present its feasibility.},
	isbn = {978-1-4244-5604-8},
	doi = {10.1109/NETGAMES.2009.5446220},
	author = {Beskow, Paul and Erikstad, Geir and Halvorsen, P{\r a}l and Griwodz, Carsten},
	editor = {Abdallah, Maha}
}
@inproceedings {Simula.ND.263,
	title = {Evaluating the Run-Time Performance of Kahn Process Network Implementation Techniques on Shared-Memory Multiprocessors},
	journal = {Complex, Intelligent and Software Intensive Systems, International Conference},
	year = {2009},
	pages = {639-644},
	publisher = {IEEE Computer Society},
	type = {Workshop},
	abstract = {Software development tools have not adapted to the growing popularity of multi-core CPUs, and developers are still {\textquoteleft}{\textquoteleft}stuck\&$\#$39;\&$\#$39; with low-level and high-cost thread abstractions. The situation is becoming even more complicated with the advent of heterogenuous computing. In this article, we point out some drawbacks of high-level abstractions currently in use, and propose Kahn process networks (KPN) as a more high-level and efficient abstraction for developing parallel applications. We show that the native POSIX mechanisms (threads and message queues) perform suboptimally as an implementation vehicle for KPNs, and we present an implementation of a run-time environment that can execute KPNs with less overhead. Our evaluation shows the advantages and disadvantages of statically mapping Kahn processes to CPUs.},
	isbn = {978-0-7695-3575-3},
	doi = {10.1109/CISIS.2009.43},
	author = {Vrba, Zeljko and Halvorsen, P{\r a}l and Griwodz, Carsten}
}
@inproceedings {Simula.ND.323,
	title = {Fine-Grained Scalable Streaming From Coarse-Grained Videos},
	journal = {International Workshop on Network and Operating Systems Support for Digital Audio and Video (NOSSDAV)},
	year = {2009},
	month = {June},
	pages = {103-108},
	publisher = {ACM},
	type = {Conference},
	abstract = {Scalable video is an attractive option for adapting the bandwidth consumption of streaming video to the available bandwidth. Fine-grained scalability can adapt most closely to the available bandwidth, but this comes at the cost of a high compression penalty. In the context of VoD streaming to mobile end systems, we have therefore explored whether a similar adaptation to the available bandwidth can be achieved by performing layer switching in coarse-grained scalable videos. In this approach, enhancement layers of a video stream are switched on and off to achieve any desired longer-term bandwidth. We performed user studies to evaluate the idea, and came to the far-from-obvious conclusion that layer switching is viable way for bit-rate savings and fine-grained bit-rate adaptation even for rather short times between layer switches.},
	isbn = {978-1-60558-433-1},
	author = {Ni, Pengpeng and Eichhorn, Alexander and Griwodz, Carsten and Halvorsen, P{\r a}l},
	editor = {Dongyan Xu Wei Tsa {Ooi}}
}
@inproceedings {Simula.ND.399,
	title = {Improving Disk I/O Performance on Linux},
	journal = {UpTimes - Proceedings of Linux-Kongress and OpenSolaris Developer Conference 2009},
	number = {2},
	year = {2009},
	month = {October},
	pages = {61-70},
	publisher = {German Unix User Group},
	type = {Workshop},
	abstract = {The existing Linux disk schedulers are in general efficient, but we have identified two scenarios where we have observed a non-optimal behavior. The first is when an application requires a fixed bandwidth, and the second is when an operation performs a file tree traversal. In this paper, we address both these scenarios and propose solutions which both increase performance.},
	isbn = {978-3-86541-358-1},
	author = {Carl Henrik {Lunde} and Espeland, H{\r a}vard and H{\r a}kon Kvale {Stensland} and Petlund, Andreas and Halvorsen, P{\r a}l},
	editor = {Wetter, Dirk}
}
@inproceedings {Simula.ND.407,
	title = {Improving File Tree Traversal Performance by Scheduling I/O Operations in User Space},
	journal = {Proceedings of the 28th IEEE International Performance Computing and Communications Conference (IPCCC)},
	year = {2009},
	pages = {145-152},
	publisher = {IEEE},
	type = {Conference},
	abstract = {Current in-kernel disk schedulers provide efficient means to optimize the order (and minimize disk seeks) of issued, in-queue I/O requests. However, they fail to optimize sequential multi-file operations, like traversing a large file tree, because only requests from one file are available in the scheduling queue at a time. We have therefore investigated a user-level, I/O request sorting approach to reduce inter-file disk arm movements. This is achieved by allowing applications to utilize the placement of inodes and disk blocks to make a one sweep schedule for all file I/Os requested by a process, i.e., data placement information is read first before issuing the low-level I/O requests to the storage system. Our experiments with a modified version of tar show reduced disk arm movements and large performance improvements.},
	isbn = {978-1-4244-5736-6},
	author = {Carl Henrik {Lunde} and Espeland, H{\r a}vard and H{\r a}kon Kvale {Stensland} and Halvorsen, P{\r a}l},
	editor = {Zhong, Sheng}
}
@article {Simula.ND.311,
	title = {Improving SCTP Retransmission Delays for Time-Dependent Thin Streams},
	journal = {Multimedia Tools and Applications},
	volume = {45},
	number = {1-3},
	year = {2009},
	note = {Special Issue on Massively Multiuser Online Gaming Systems and Applications},
	pages = {33-60},
	abstract = {A large number of network services rely on IP and reliable transport pro- tocols. For applications that provide abundant data for transmission, loss is usually handled satisfactorily, even if the application is latency-sensitive. For data streams where small packets are sent intermittently, however, applications can occasionally experience extreme latencies. As it is not uncommon that such thin-stream ap- plications are time-dependent, any unnecessarily induced delay can have severe conse- quences for the service provided. It has been shown that TCP has several shortcomings with respect to the latency requirements of thin streams because of the way it handles retransmissions. As such, an alternative to TCP may be SCTP, which was de- veloped to meet the requirements of signalling transport. SCTP has subsequently been considered more appropriate than TCP for congestion-controlled streaming, primarily because SCTP maintains packetboundaries and intrinsically supports partial reliabil- ity. In this paper, we evaluate the Linux-kernel SCTP implementation in the context of thin streams. To address the identi{fi}ed latency challenges, we propose sender-side only enhancements that reduce the application-layer latency in a manner that is compatible with unmodi{fi}ed receivers. These enhancements can be switched on by applications and are used only when the system identi{fi}es the stream as thin. To evaluate the latency performance, we have performed several tests over various real networks and over an emulated network, varying parameters like RTT, packet loss and amount of competing cross tra{ffi}c. When comparing our modi{fi}cations with SCTP on Linux and FreeBSD and TCP New Reno, our results show great latency improvements and indicate the need for a separate handling of thin and thick streams.},
	doi = {10.1007/s11042-009-0286-8},
	author = {Petlund, Andreas and Beskow, Paul and Pedersen, Jon and Espen S{\o}g{\r a}rd {Paaby} and Griwodz, Carsten and Halvorsen, P{\r a}l}
}
@inproceedings {Simula.ND.219,
	title = {On the Influence of Latency Estimation on Dynamic Group Communication Using Overlays},
	journal = {Proceedings of Multimedia Computing and Networking (MMCN)},
	volume = {7253},
	year = {2009},
	publisher = {SPIE},
	type = {Conference},
	abstract = {Distributed interactive applications tend to have stringent latency requirements and some may have high bandwidth demands. Many of them have also very dynamic user groups for which all-to-all communication is needed. In online multiplayer games, for example, such groups are determined through region-of-interest management in the application. We have investigated a variety of group management approaches for overlay networks in earlier work and shown that several useful tree heuristics exist. However, these heuristics require full knowledge of all overlay link latencies. Since this is not scalable, we investigate the effects that latency estimation techniques have on the quality of overlay tree constructions. We do this by evaluating one example of our group management approaches in Planetlab and examining how latency estimation techniques influence their quality. Specifically, we investigate how two well-known latency estimation techniques, Vivaldi and Netvigator, affect the quality of tree building.},
	isbn = {9780819475039},
	doi = {10.1117/12.815561},
	author = {Vik, Knut-Helge and Griwodz, Carsten and Halvorsen, P{\r a}l},
	editor = {Ketan Mayer-Pate {Rejaie}}
}
@inproceedings {Simula.ND.321,
	title = {Kahn Process Networks Are a Flexible Alternative to MapReduce},
	journal = {Proceedings of 11th IEEE International Conference on High Performance Computing and Communications (HPCC)},
	year = {2009},
	pages = {154-162},
	publisher = {IEEE Computer Society},
	type = {Conference},
	abstract = {Experience has shown that development using shared-memory concurrency, the prevalent parallel programming paradigm today, is hard and synchronization primitives nonintuitive because they are low-level and inherently nondeterministic. To help developers, we propose Kahn process networks, which are based on message-passing and shared-nothing model, as a simple and flexible tool for modeling parallel applications. We argue that they are more flexbile than MapReduce, which is widely recognized for its efficiency and simplicity. Nevertheless, Kahn process networks are equally intuitive to use, and, indeed, MapReduce is implementable as a Kahn process network. Our presented benchmarks (word count and k-means) show that a Kahn process network framework permits alternative implementations that bring significant performance advantages: the two programs run by a factor of up to \sim 2.8 (word-count) and \sim 1.8 (k-means) faster than their implementations for Phoenix, which is a MapReduce framework specifically optimized for executing on multicore machines.},
	isbn = {978-0-7695-3738-2},
	doi = {10.1109/HPCC.2009.46},
	author = {Vrba, Zeljko and Beskow, Paul and Halvorsen, P{\r a}l and Griwodz, Carsten}
}
@inproceedings {Simula.ND.325,
	title = {Limits of Work-Stealing Scheduling},
	journal = {Job Scheduling Strategies for Parallel Processing (14th International Workshop, 2009)},
	year = {2009},
	pages = {280-299},
	publisher = {Springer Berlin / Heidelberg},
	type = {Workshop},
	abstract = {The number of applications with many parallel cooperating processes is steadily increasing, and developing efficient runtimes for their execution is an important task. Several frameworks have been developed, such as MapReduce and Dryad, but developing scheduling mechanisms that take into account processing \emph{and} communication requirements is hard. In this paper, we explore the limits of work stealing scheduler, which has empirically been shown to perform well, and evaluate load-balancing based on graph partitioning as an orthogonal approach. All the algorithms are implemented in our Nornir runtime system, and our experiments on a multi-core workstation machine show that the main cause of performance degradation of work stealing is when very little processing time, which we quantify exactly, is performed per message. This is the type of workload in which graph partitioning has the potential to achieve better performance than work-stealing.},
	isbn = {978-3-642-04632-2},
	doi = {10.1007/978-3-642-04633-9\_15},
	author = {Vrba, Zeljko and Espeland, H{\r a}vard and Halvorsen, P{\r a}l and Griwodz, Carsten},
	editor = {Frachtenberg, Eitan and Schwiegelshohn, Uwe}
}
@inproceedings {Simula.ND.369,
	title = {A Network-Layer Proxy for Bandwidth Aggregation and Reduction of IP Packet Reordering},
	journal = {The 34rd Annual IEEE Conference on Local Computer Networks (LCN)},
	year = {2009},
	month = {July},
	pages = {585-592},
	publisher = {IEEE},
	type = {Conference},
	abstract = {With today\&$\#$39;s widespread deployment of wireless technologies, it is often the case that a single communication device can select from a variety of access networks. At the same time, there is an ongoing trend towards integration of multiple network interfaces into end-hosts, such as cell phones with HSDPA, Bluetooth and WLAN. By using multiple Internet connections concurrently, network applications can benefit from aggregated bandwidth and increased fault tolerance. However, the heterogeneity of wireless environments introduce challenges with respect to implementation, deployment, and protocol compatibility. Variable link characteristics cause reordering when sending IP packets of the same flow over multiple paths. This paper introduces a multilink proxy that is able to transparently stripe traffic destined for multihomed clients. Operating on the network layer, the proxy uses path monitoring statistics to adapt to changes in throughput and latency. Experimental results obtained from a proof-of-concept implementation verify that our approach is able to fully aggregate the throughput of heterogeneous downlink streams, even if the path characteristics change over time. In addition, our novel method of equalizing delays by buffering packets on the proxy significantly reduces IP packet reordering and the buffer requirements of clients.},
	isbn = {978-1-4244-4488-5},
	doi = {10.1109/LCN.2009.5355198},
	author = {Evensen, Kristian and Kaspar, Dominik and Paal Einar {Engelstad} and Audun Fosselie {Hansen} and Griwodz, Carsten and Halvorsen, P{\r a}l}
}
@inproceedings {Simula.ND.397,
	title = {The Nornir Run-Time System for Parallel Programs Using Kahn Process Networks},
	journal = {Proceedings of 6th International Conference on Network and Parallel Computing (NPC)},
	year = {2009},
	pages = {1-8},
	publisher = {IEEE Computer Society},
	type = {Conference},
	abstract = {Shared-memory concurrency is the prevalent paradigm used for developing parallel applications targeted towards small- and middle-sized machines, but experience has shown that it is hard to use. This is largely caused by synchronization primitives which are low-level, inherently nondeterministic, and, consequently, non-intuitive to use. In this paper, we present the \textit{Nornir} run-time system. Nornir is comparable to well-known frameworks like MapReduce and Dryad, but has additional support for process structures containing cycles. It is based on the formalism of Kahn process networks, which we deem as a simple and deterministic alternative to shared-memory concurrency. Experiments with real and synthetic benchmarks on up to 8 CPUs show that performance in most cases improves almost linearly with the number of CPUs, when not limited by data dependencies.},
	isbn = {978-0-7695-3837-2},
	author = {Vrba, Zeljko and Halvorsen, P{\r a}l and Griwodz, Carsten and Beskow, Paul and Johansen, Dag}
}
@article {Simula.ND.327,
	title = {The Partial Migration of Game State and Dynamic Server Selection to Reduce Latency},
	journal = {Multimedia Tools and Applications},
	volume = {45},
	number = {1-3},
	year = {2009},
	note = {Special Issue on Massively Multiuser Online Gaming Systems and Applications},
	pages = {83-107},
	abstract = {Massively multi-player online games (MMOGs) have stringent latency requirements and must support large numbers of concurrent players. To handle these conflicting requirements, it is common to divide the virtual environment into virtual regions. As MMOGs are world-spanning games, it is plausible to disperse these regions on geographically distributed servers. Core selection can then be applied to locate an optimal server for placing a region, based on player latencies. Functionality for migrating objects supports this objective, with a distributed name server ensuring that references to the moved objects are maintained. As a result we anticipate a decrease in the aggregate latency for the affected players. The core selection relies on a set of servers and measurements of the interacting players latencies. Measuring these latencies by actively probing the network is not scalable for a large number of players. We therefore explore the use of latency estimation techniques to gather this information.},
	doi = {10.1007/s11042-009-0287-7},
	author = {Beskow, Paul and Vik, Knut-Helge and Halvorsen, P{\r a}l and Griwodz, Carsten}
}
@inbook {Simula.ND.305,
	title = {RELAY - on the Performance and Resource Utilization of Time-Dependent Large-Scale Distributed Systems},
	booktitle = {Simula Research Laboratory - by thinking constantly about it},
	year = {2009},
	pages = {199-236},
	publisher = {Springer},
	organization = {Springer},
	chapter = {17},
	address = {Heidelberg},
	abstract = {Powerful end-systems and faster access networks make large-scale distributed multimedia applications such as streaming and gaming increasingly popular. This popularity does, of course, also mean that the increase in available computing power and network bandwidth does not solve all existing problems, but rather that other parts of distributed systems will become bottlenecks. To relieve these, RELAY addresses issues of resource utilization in such distributed systems by investigating network and operating system support that provides quantifiably better support than the state-of-the-art. One of our main goals is to integrate and combine mechanisms to get more scalable, less resource demanding, high performance systems for time-dependent large-scale distributed multimedia systems. RELAY designs, implements and evaluates algorithms, mechanisms and tools to improve resource utilization, increase throughput, reduce/hide latency and support soft Quality-of-Service. The development takes user experience into account, since adaptation specific to this can reduce the necessary resource consumption considerably. We consider architectural, application-level, kernel and protocol support to achieve our goals, and we investigate combinations of performance-enhancing mechanisms such that they do not counteract each other. RELAY{\textquoteright}s approach is application-driven, where the best way of achieving performance improvements determines the research methodology. As an example, we report several of our findings in investigating support for distributed interactive applications, and massive multiplayer games in particular.},
	isbn = {978-3642011559},
	author = {Griwodz, Carsten and Halvorsen, P{\r a}l},
	editor = {Tveito, Aslak and Are Magnus {Bruaset} and Lysne, Olav}
}
@inproceedings {Simula.nd.473,
	title = {Video Streaming: History, Current Trends and Future Visions (keynote Abstract)},
	journal = {Proceedings of the World Academy of Science, Engineering and Technology (WASET)},
	volume = {55},
	year = {2009},
	month = {July},
	pages = {1},
	publisher = {WASET},
	type = {Conference},
	abstract = {VIDEO STREAMING has been a hot research topic for many years, and the technology is now mature enough to offer such services to the end-users over the Internet. At the University of Oslo and Simula Research Laboratory, we have worked in this area for more than a decade, and this talk presents some of our experiences in this area and points out our future vision in the area of video delivery. Early approaches used single server systems where the focus of the research often was efficient utilization of the machine resources and timely data retrieval, i.e., trying to take into account application characteristics, content popularity and user behavior. Single server systems are still in use today, but due to performance and scalability challenges, researchers moved to server clusters, hierarchical architectures and multicast mechanisms - and combinations of these. Thus, we have to day a wide range of systems including server-based systems, e.g., as used by video community services like YouTube, and peer-to-peer systems, e.g., as used by Internet TV providers like PPLive. Examples where hierarchical architectures combined with ideas from BitTorrent, like Move [1] and SmoothStreaming [2], also prove to be very scalable. With respect to the next generation video streaming system, we envision that there will be a close integration of emerging search, recommender and social networking systems. This will raise new functional requirements to the streaming services, e.g., selecting arbitrary clips from different video sequences, combining these with user generated media and playing the whole clip as one personalized video. Additionally, these systems must deal with a lot of heterogeneity, e.g., users access video content over various networks, and the streamed content may be viewed on different displays ranging from small, mobile hand-helds to high-definition home theatres. In this part of the talk, we also give a presentation of DAVVI [3]. This is a prototype of our next generation multimedia entertainment platform providing a personalized, topic-based user experience blurring the distinction between content producers and consumers. It delivers multi-quality video content in a torrent-similar way over HTTP. Thus, small segments of each video is retrieved from possibly different locations where the quality of the video is adapted to the available resources. Furthermore, through applied search, personalization and rec- ommendation technologies, end-users can efficiently search and retrieve highlights and combine arbitrary events in a customized manner using drag and drop creating playlists of video segments, i.e., providing a brand new, personalized user experience.},
	isbn = {ISSN 2070-3724},
	author = {Halvorsen, P{\r a}l},
	editor = {Ardil, Cemal}
}
@inproceedings {Simula.ND.371,
	title = {Video Streaming Into Virtual Worlds: the Effects of Virtual Screen Distance and Angle on Perceived Quality},
	journal = {ACM Multimedia Conference},
	year = {2009},
	note = {Short paper.},
	month = {October},
	pages = {885-888},
	publisher = {ACM},
	type = {Conference},
	abstract = {There is an increasing trend to include streamed video data in 3D environments. Such environments allow potentially several concurrently visible videos on a single display device, and consequently, network and processing bottlenecks. As a first step towards an avoidance of such problems, we have performed subjective assessments using a 3D application prototype to determine how positioning of video in the 3D environment influences the user perception of reduced quality videos. Using video clips from several genres, we have compared the influence of various ways to reduce video quality and users{\textquoteright} perception of degraded quality. We evaluated the influence of distance and angle of the placement.},
	isbn = {978-1-60558-608-3},
	doi = {10.1145/1631272.1631439},
	author = {Ni, Pengpeng and Gaarder, Fredrik and Griwodz, Carsten and Halvorsen, P{\r a}l},
	editor = {Gao, Wen and Rui, Yong and Hanjalic, Alan and Xu, Changsheng and Steinbach, Eckehard and Abdulmotaleb El {Saddik} and Zhou, Michelle}
}
@inproceedings {Simula.ND.227,
	title = {An Architecture for Adaptive Multimedia Streaming to Mobile Nodes},
	journal = {Proceedings of International Conference on Advances in Mobile Computing \& Multimedia (MoMM)},
	year = {2008},
	month = {November},
	pages = {313-316},
	publisher = {ACM},
	type = {Conference},
	abstract = {We describe the {\adimus} architecture which addresses the problem of maintaining the subjective quality of multimedia streaming for a mobile user. In contrast to other works, the entire end-to-end path of the video stream is considered. Adaptation mechanisms for maintaining quality include time-critical handovers, overlay routing and network estimation techniques. Our architecture is built on overlays that provides the necessary functionality for a video streaming service. The paper highlights the key components that ADIMUS advocates to support quality streaming from server to mobile client.},
	isbn = {978-1-60558-269-6},
	author = {Leister, Wolfgang and Sutinen, Tiia and Boudko, Svetlana and Marsh, Ian and Griwodz, Carsten and Halvorsen, P{\r a}l},
	editor = {Kotsis, Gabriele and Taniar, David and Pardede, Eric and Khalil, Ismail}
}
@inproceedings {Simula.ND.119,
	title = {A Benchmarking System for Multipath Overlay Multimedia Streaming},
	journal = {IEEE International Conference on Multimedia \& Expo (ICME)},
	year = {2008},
	month = {June},
	pages = {853-856},
	publisher = {IEEE},
	type = {Conference},
	abstract = {The rapid growth of the Internet multimedia services brings new challenges to how multimedia streams can be delivered to the users over bandwidth-constraint networks. Different strategies that exploit multipath streaming in order to provide better utilization of the Internet resources have been proposed by the research community. However, there exists no metric that allows us to evaluate how close these strategies are to the optimal resource utilization. This paper proposes a static benchmarking system that models the best possible distribution of streams along multiple paths in an overlay network that is shared by several senders and receivers. We have tested it with several different network topologies, and present the test results in this paper.},
	isbn = {978-1-4244-2570-9},
	author = {Boudko, Svetlana and Leister, Wolfgang and Griwodz, Carsten and Halvorsen, P{\r a}l},
	editor = {Ostermann, J{\"o}rn and Ebrahimi, Touradj and Naphade, Milind and Fitzek, Frank and Rahardja, Susanto and Rosenhahn, Bodo and Smeulders, Arnold}
}
@inproceedings {Simula.ND.221,
	title = {Constructing Low-Latency Overlay Networks: Tree Vs. Mesh Algorithms},
	journal = {Proceedings of IEEE Conference on Local Computer Networks (LCN)},
	year = {2008},
	month = {October},
	pages = {36-43},
	publisher = {IEEE},
	type = {Conference},
	abstract = {Distributed interactive applications may have stringent latency requirements and dynamic user groups. These applications may benefit from a group communication system, and to improve the system support for such applications, we investigate graph algorithms that construct low-latency overlay networks for application-layer multicast. In particular, we focus on reducing the diameter and the pair-wise latencies in the overlay. The overlay construction time is also considered, as it is often time-dependent in our dynamic target applications. Here, we have implemented and experimentally analyzed spanning-tree heuristics and mesh construction heuristics, and compared their performance and applicability to distributed interactive applications. We found that trees are faster to construct and save considerable amounts of resources in the network. Meshes, on the other hand, yield lower pair-wise latencies and increases the fault tolerance, but at the expense of increased resource consumption.},
	isbn = {978-1-4244-2412-2},
	doi = {10.1109/LCN.2008.4664149},
	author = {Vik, Knut-Helge and Griwodz, Carsten and Halvorsen, P{\r a}l},
	editor = {Elmallah, Ehab and Younis, Mohamed and Chun Tung {Chou}}
}
@article {Simula.ND.102,
	title = {Evaluating Steiner Tree Heuristics and Diameter Variations for Application Layer Multicast},
	journal = {Computer Networks},
	volume = {52},
	number = {15},
	year = {2008},
	note = {Special issue on Complex Computer and Communication Networks, Elsevier},
	month = {October},
	pages = {2872-2893},
	abstract = {Latency reduction in distributed interactive applications has been studied intensively. Such applications may have stringent latency requirements and dynamic user groups. We focus on application-layer multicast with a centralized approach to the group management. The groups are organized in overlay networks that are created using graph algorithms that create a tree structure for the group. A tree has no cycles and uses a small routing table, as opposed to a connected overlay mesh. We investigate a group of spanning tree problems that are referred to as Steiner tree problems, and we have a particular focus on reducing the diameter of a tree, which is the maximum pairwise latency in a tree. In addition, we focus on reducing the time it takes to execute membership changes. In that context, we use core-selection heuristics to find well-placed client nodes, and edge-pruning algorithms to reduce the number of edges in an otherwise fully meshed overlay. Our edge-pruning algorithms strongly connect well-placed client nodes to the remaining group members, to create new and pruned group graphs. Consequently, when a tree algorithm is applied to a pruned group graph, it is manipulated into creating trees with a smaller diameter.We devised new Steiner-tree heuristics that reduced the diameter, and also proposed new edge-pruning algorithms to make the tree construction faster. These heuristics and algorithms were implemented and analyzed experimentally along with several spanning-tree and core-selection heuristics found in the literature. We found that a full-mesh of shortest paths makes it difficult for Steiner-tree heuristics to find better trees than spanning tree algorithms. The network seen from the application layer is in fact a full mesh of shortest paths. In addition, we found that faster Steiner-tree heuristics that do not explicitly optimize the diameter are able to compete with slower heuristics that do optimize it.},
	doi = {10.1016/j.comnet.2008.06.003},
	author = {Vik, Knut-Helge and Halvorsen, P{\r a}l and Griwodz, Carsten}
}
@inproceedings {Simula.ND.111,
	title = {Evaluation of Multi-Core Scheduling Mechanisms for Heterogeneous Processing Architectures},
	journal = {Network and Operating System Support for Digital Audio and Video (NOSSDAV 2008)},
	year = {2008},
	month = {May},
	pages = {33-38},
	publisher = {ACM},
	type = {Workshop},
	abstract = {General-purpose CPUs with multiple cores are established products, and new heterogeneous technology like the Cell broadband engine and general-purpose GPUs bring an even higher degree of true multi-processing into the market. However, means for utilizing the processing power is immature. Current tools typically assume that exclusive use of these resources is sufficient, but this assumption will soon be invalid because the interest in using their processing power for general-purpose tasks. Among the applications that can benefit from such technology is transcoding support for distributed media applications, where remote participants join and leave dynamically. Transcoding consists of several clearly separated processing operations that consume a lot of resources, such that individual processing units are unable to handle all operations of a session of arbitrary size. The individual operations can then be distributed over several processing units, and data must be moved between them according to the dependencies between operations. Many multi-processor scheduling approaches exist, but to the best of our knowledge, a challenge is still to find mechanisms that can schedule dynamic workloads of communicating operations while taking both the processing and communication requirements into account. For such applications, we believe that feasible scheduling can be performed in two levels, i.e., divided into the task of placing a job onto a processing unit and the task of multitasking time-slices within a single processing unit. We have implemented some simple high-level scheduling mechanisms and simulated a video conferencing scenario running on topologies inspired by existing systems from Intel, AMD, IBM and nVidia. Our results show the importance of using an efficient high-level scheduler.},
	isbn = {978-1-60588-157-6},
	author = {H{\r a}kon Kvale {Stensland} and Griwodz, Carsten and Halvorsen, P{\r a}l},
	editor = {Griwodz, Carsten and Wolf, Lars}
}
@inproceedings {Simula.ND.185,
	title = {Improving Application Layer Latency for Reliable Thin-Stream Game Traffic},
	journal = {Netgames, Worcester, Ma. US, 2008},
	year = {2008},
	publisher = {Association for Computing Machinery (ACM)},
	type = {Workshop},
	abstract = {A wide range of networked games send data with very high interarrival-time between packets and with small payloads in each packet. We call these transmission patterns {\textquoteleft}{\textquoteleft}thin streams{\textquoteright}{\textquoteright}. Reliability, when needed for game traffic, is usually achieved through TCP or by using retransmission schemes modelled on TCP. These retransmission schemes can result in very large delays if the stream is thin. Viewed in the light of the time-dependent nature of game traffic, large delays can be severely impeding to the game experience. In order to reduce application-layer latency when packets are lost, we have implemented modifications to TCP in the Linux kernel. The changes are only active when thin-stream properties are detected, thus not affecting TCP behaviour when the stream is not thin. In this paper, we show the latency improvements from these thin-stream modifications. As a case study, we have used the game BZFlag to test the mechanisms, and present statistics from these tests. The experimental results show that our modifications allow TCP to recover earlier from packet loss. This latency reduction was then shown to improve the difference between perceived and actual player positions in the BzFlag game.},
	isbn = {978-1-60558-132-3},
	author = {Petlund, Andreas and Halvorsen, P{\r a}l and Griwodz, Carsten},
	editor = {Claypool, Mark}
}
@inproceedings {Simula.ND.261,
	title = {Latency Reducing TCP Modifications for Thin-Stream Interactive Applications},
	journal = {UpTimes - Magazine of the German Unix User Group (Proceedings of Linux Kongress 2008)},
	number = {2},
	year = {2008},
	month = {10},
	pages = {150-154},
	publisher = {German Unix User Group},
	type = {Workshop},
	address = {Bachemer Str. 12, 50931 K{\"o}ln},
	abstract = {A wide range of Internet-based services that use reliable transport protocols display what we call thin-stream properties. This means that the application sends data with such a low rate that the retransmission mechanisms of the transport protocol are not fully effective. In time-dependent scenarios (like online games, control systems or some sensor networks) where the user experience depends on the data delivery latency, packet loss can be devastating for the service quality. Extreme latencies are caused by TCP{\textquoteright}s dependency on the arrival of new data from the application to trigger retransmissions effectively through fast retransmit instead of waiting for long timeouts. In order to reduce application-layer latency when packets are lost, we have implemented modifications to the TCP retransmission mechanisms in the Linux kernel. We have also implemented a bundling mechanisms that introduces redundancy in order to preempt the experience of packet loss. In short, if the kernel detects a thin stream, we trade a small amount of bandwidth for latency reduction and apply: Removal of exponential backoff: To prevent an exponential increase in retransmission delay for a repeatedly lost packet, we remove the exponential factor. Faster Fast Retransmit: Instead of waiting for 3 duplicate acknowledgments before sending a fast retransmission, we retransmit after receiving only one. Redundant Data Bundling: We copy (bundle) data from the unacknowledged packets in the send buffer into the next packet if space is available. These enhancements are applied only if the stream is detected as thin. This is accomplished by defining thresholds for packet size and packets in flight. Also, we consider the redundancy introduced by our mechanisms acceptable because the streams are so thin that normal congestion mechanisms do not come into effect. We have implemented these changes in the Linux kernel (2.6.23.8), and have tested the modifications on a wide range of different thin-stream applications (Skype, BZFlag, SSH, ...) under varying network conditions. The modifications are made available as a patch. Our results show that applications which use TCP for interactive time-dependent traffic will experience a reduction in both maximum and average latency, giving the users quicker feedback to their interactions. Availability of this kind of mechanisms will give Linux an edge when it comes to providing customizability for interactive network services. The quickly growing market for Linux gaming may benefit from lowered latency. As an example, most of the large MMORPG{\textquoteright}s today use TCP (like World of Warcraft and Age of Conan) and several multimedia applications (like Skype) use TCP fallback if UDP is blocked. The talk will outline the different aspects of using TCP for interactive time-dependent applications. We will present statistics from network traces from a range of thin-stream applications. A description of our developed mechanisms will be presented and compared to other related TCP modifications. We will also present the results from extensive tests performed using our modifications. We can also demonstrate our modifications.},
	isbn = {978-3-86541-300-0},
	author = {Petlund, Andreas and Evensen, Kristian and Griwodz, Carsten and Halvorsen, P{\r a}l},
	editor = {Stief, W.}
}
@inproceedings {Simula.ND.225,
	title = {Latency Reduction by Dynamic Core Selection and Partial Migration of Game State},
	journal = {Proceedings of Workshop on Network and Systems Support for Games (NetGames)},
	year = {2008},
	month = {October},
	pages = {79-84},
	publisher = {ACM},
	type = {Workshop},
	abstract = {Massively multi-player online games (MMOGs) require low latency while supporting a large number of concurrent players, often sharing one worldwide instance of the game. As these are conflicting requirements, a common way of distributing load is by dividing the virtual environment into virtual regions. As MMOGs are world-spanning games, it is plausible to disperse these regions on geographically distributed servers. As such, we propose the use of core selection for finding an optimal server for placing a region, and support for migrating the game state to that server. The first goal relies on a set of servers and measurement of the interacting players latencies. In locating an optimal server, we anticipate a decrease in the overall latency for the majority of players. This reduction occurs by migrating the region to a server closer in proximity to the majority of players in that virtual region, thereby lowering the response time of any interaction.},
	isbn = {978-1-60558-132-3},
	author = {Beskow, Paul and Vik, Knut-Helge and Halvorsen, P{\r a}l and Griwodz, Carsten},
	editor = {Claypool, Mark}
}
@inproceedings {Simula.ND.73,
	title = {Multicast Tree Diameter for Dynamic Distributed Interactive Applications},
	journal = {IEEE International Conference on Computer Communications - IEEE INFOCOM},
	year = {2008},
	month = {April},
	pages = {1597-1605},
	publisher = {IEEE},
	type = {Annual},
	edition = {27th},
	abstract = {Considerable attention has been given to latency reduction in distributed interactive applications. Such applications may have stringent latency requirements and dynamic user groups. In this paper, our focus has been on using application layer multicast with a centralized approach to the group management. The groups are organized in overlay networks that are created using graph algorithms. We investigate many spanning tree problems with particular focus on reducing the diameter of a tree, i.e., the maximum pairwise latency between users. In addition, we focus on reducing the time it takes to execute membership changes. In that context, we use core selection heuristics to find well located group nodes, and edge pruning algorithms to reduce the number of edges in an otherwise fully meshed overlay. Our edge pruning algorithms strongly connect well located group nodes to the remaining group members, to create new and pruned group graphs. Such that, when a tree algorithm is given a pruned group graph, it is manipulated into creating trees with lower diameter. In the investigation presented here, we have implemented and experimentally analyzed spanning tree heuristics, core selection heuristics and edge pruning algorithms. We find that faster heuristics that do not explicitly optimize the diameter are able to compete with slower heuristics that optimize the diameter.},
	doi = {10.1109/INFOCOM.2008.220},
	author = {Vik, Knut-Helge and Halvorsen, P{\r a}l and Griwodz, Carsten},
	editor = {Merill, Douglas and Saha, Debanjan and Jennifer C. {Hou} and Kalyanaraman, Shivkumar and Sivalingam, Krishna}
}
@inproceedings {Simula.ND.118,
	title = {Performance Measurements and Evaluation of Video Streaming in HSDPA Networks With 16QAM Modulation},
	journal = {IEEE International Conference on Multimedia \& Expo (ICME)},
	year = {2008},
	month = {June},
	publisher = {IEEE},
	type = {Conference},
	abstract = {The High-Speed Downlink Packet Access (HSDPA) communication protocol improves downlink performance on mobile networks and is currently being deployed in networks around the world. In Norway, two operators started offering this service in 2007. This article discusses performance measurements done in Telenor{\textquoteright}s HSDPA network in Oslo in the context of video streaming. In particular, we present the results of streaming experiments measuring characteristics such as packet loss, latency, jitter and bit-errors. Based on this data, we evaluate the HSDPA network{\textquoteright}s suitability for real-time video streaming, and discuss what can be done to improve the quality of video streaming under the observed network characteristics.},
	isbn = {978-1-4244-2570-9},
	author = {Riiser, Haakon and Halvorsen, P{\r a}l and Griwodz, Carsten and Hestnes, Bj{\o}rn},
	editor = {Ostermann, J{\"o}rn and Ebrahimi, Touradj and Naphade, Milind and Fitzek, Frank and Rahardja, Susanto and Rosenhahn, Bodo and Smeulders, Arnold}
}
@article {Simula.ND.83,
	title = {Redundant Bundling in TCP to Reduce Perceived Latency for Time-Dependent Thin Streams},
	journal = {IEEE Communications Letters},
	volume = {12},
	number = {4},
	year = {2008},
	month = {4},
	pages = {334 - 336},
	abstract = {TCP and UDP are the dominant transport protocols today, with TCP being preferred because of the lack of fairness mechanisms in UDP. Some time-dependent applications with small bandwidth requirements, however, occationally suffer from unnecessarily high latency due to TCP retransmission mechanisms that are optimized for high-throughput streams. Examples of such thin-stream applications are Internet telephony and multiplayer games. For such interactive applications, the high delays can be devastating to the experience of the service. To address the latency issues, we explored application-transparent, sender-side modifications. We investigated whether it is possible to bundle unacknowledged data to preempt the experience of packet loss and improve the perceived latency in time-dependent systems. We implemented and tested this idea in Linux. Our results show that we can reduce the application latency by trading it against bandwidth.},
	author = {Evensen, Kristian and Petlund, Andreas and Griwodz, Carsten and Halvorsen, P{\r a}l}
}
@inproceedings {Simula.ND.112,
	title = {TCP Enhancements for Interactive Thin-Stream Applications},
	journal = {Network and Operating Systems Support for Digital Audio and Video (NOSSDAV 2008)},
	year = {2008},
	note = {short paper and demo},
	month = {May},
	pages = {127-128},
	publisher = {ACM},
	type = {Workshop},
	abstract = {TCP is frequently used for interactive multimedia applications like online games and voice-over-IP (VoIP) due to firewall issues and fairness considerations. However, traffic analysis shows that these streams usually have small packets and a low packet rate, and that in case of loss, severe latency penalties occur for all existing TCP variations in Linux. In this demonstration, we show how small, efficient TCP enhancements greatly improve the perceived quality of such low latency, interactive applications.},
	isbn = {978-1-60588-157-6},
	author = {Petlund, Andreas and Evensen, Kristian and Griwodz, Carsten and Halvorsen, P{\r a}l},
	editor = {Griwodz, Carsten and Wolf, Lars}
}
@inproceedings {Simula.ND.159,
	title = {TCP Mechanisms for Improving the User Experience for Time-Dependent Thin-Stream Applications},
	journal = {The 33rd Annual IEEE Conference on Local Computer Networks (LCN)},
	year = {2008},
	publisher = {IEEE},
	type = {Conference},
	abstract = {A wide range of Internet-based services that use reliable transport protocols display what we call thin-stream properties. This means that the application sends data with such a low rate that the retransmission mechanisms of the transport protocol are not fully effective. In time-dependent scenarios where the user experience depends on the data delivery latency, packet loss can be devastating for the service quality. In order to reduce application-layer latency when packets are lost, we have implemented modifications to the TCP retransmission mechanisms in the Linux kernel. The changes are only active when thin-stream properties are detected, thus not affecting TCP behaviour when the stream is not thin. In this paper, we show the latency improvements from these thin-stream modifications. We have tested several thin-stream applications like remote terminals (SSH) and audio conferencing (Skype), and we evaluate the user experience with and without the TCP modifications. Our experimental results show that our modifications allow TCP to recover earlier from packet loss. Furthermore, user surveys indicate that the majority of users easily detect improvements in the perceived quality of the tested applications.},
	isbn = {978-1-4244-2412-2},
	author = {Petlund, Andreas and Griwodz, Carsten and Halvorsen, P{\r a}l},
	editor = {Elmallah, Ehab and Younis, Mohamed and Chun Tung {Chou}}
}
@inproceedings {Simula.ND.117,
	title = {Transparent Protocol Translation and Load Balancing on a Network Processor in a Media Streaming Scenario},
	journal = {Network and Operating System Support for Digital Audio and Video (NOSSDAV 2008)},
	year = {2008},
	month = {May},
	pages = {129-130},
	publisher = {ACM},
	type = {Workshop},
	abstract = {Today, major newspapers and TV stations make live and on-demand audio/video content available, video-on-demand services are becoming common and even personal media are frequently uploaded to streaming sites. The discussion about the best transport protocol for streaming has been going on for years. Currently, HTTP-streaming is usual although the transport of streaming media data over TCP is hindered by TCP{\textquoteright}s probing behavior, which results in the rapid reduction and slow recovery of the packet rates. On the other hand, UDP has been criticized for being unfair against TCP, and it is therefore often blocked by access network providers. To exploit benefits of both TCP and UDP, we have implemented a proxy that performs transparent protocol translation in such a way that the video stream is delivered to clients in a TCP-compatible and TCP-friendly way, but with UDP-like smoothness. The translation is related to multicast-to-unicast translation and to voice-over-IP proxies that translate between UDP and TCP. Furthermore, it is also similar to the use of proxy caching that ISPs employ to reduce bandwidth demands. The unique advantage of our approach is that we avoid full-featured TCP handling on the proxy server but still achieve live protocol translation at line-speed in a TCP-compliant, TCP-friendly manner. Although we discard packets just like a sender of non-adaptive video over TCP, we achieve higher user-perceived quality because our proxy can avoid receive queue underflows in the proxy, while also achieving the same average bandwidth as a TCP connection between proxy and client. In this demo, we present our prototype implemented on an Intel IXP2400 network processor. The prototype proxy does not buffer outgoing packets, yielding data loss in case of a congested TCP side. Comparing HTTP-streaming from a web-server and RTP/UDP-streaming from a video server shows that, in case of some loss, our solution using UDP from the server and a proxy that translates to TCP delivers a smoother stream at playout rate while the end-to-end TCP stream oscillates heavily.},
	isbn = {978-1-60588-157-6},
	author = {Espeland, H{\r a}vard and Carl Henrik {Lunde} and H{\r a}kon Kvale {Stensland} and Griwodz, Carsten and Halvorsen, P{\r a}l},
	editor = {Griwodz, Carsten and Wolf, Lars}
}
@article {Simula.ND.8,
	title = {Assessment of Linux{\textquoteright} Data Path Components for Download and Streaming},
	journal = {International Journal of Software Engineering and Knowledge Engineering},
	volume = {17},
	number = {4},
	year = {2007},
	month = {August},
	pages = {456-481},
	abstract = {Distributed multimedia streaming systems are increasingly popular due to technological advances, and numerous streaming services are available today. On servers or proxy caches, there is a huge scaling challenge in supporting thousands of concurrent users that request delivery of high-rate, time-dependent data like audio and video, because this requires transfers of large amounts of data through several sub-systems within a streaming node. Unnecessary copy operations in the data path can therefore contribute significantly to the resource consumption of streaming operations. Despite previous research, off-the-shelf operating systems have only limited support for data paths that have been optimized for streaming. Additionally, system call overhead has grown with newer operating systems editions, adding to the cost of data movement. Frequently, it is argued that these issues can be ignored because of the continuing growth of CPU speeds. However, such an argument fails to take problems of modern streaming systems into account. The dissipation of heat generated by disks and high-end CPUs is a major problem of data centers, which would be alleviated if less power-hungry CPUs could be used. The power budget of mobile devices, which are increasingly used for streaming as well, is tight, and reduced power consumption an important issue. In this paper, we prove that these operations consume a large amount of resources, and we therefore revisit the data movement problem and provide a comprehensive evaluation of possible streaming data I/O paths in the Linux 2.6 kernel. We have implemented and evaluated several enhanced mechanisms and show how to provide support for more efficient memory usage and reduction of user/kernel space switches for content download and streaming applications. In particular, we are able to reduce the CPU usage by approximately 27\% compared to the best approach without kernel modifications, by removing copy operations and system calls for a streaming scenario in which RTP headers must be added to stored data for sequence numbers and timing.},
	author = {Halvorsen, P{\r a}l and Tom Anders {Dalseng} and Griwodz, Carsten}
}
@inproceedings {Simula.ND.33,
	title = {Dynamic Group Membership Management for Distributed Interactive Applications},
	journal = {32nd IEEE Conference on Local Computer Networks (LCN)},
	year = {2007},
	month = {October},
	pages = {141-148},
	publisher = {IEEE},
	type = {Conference},
	abstract = {Distributed interactive applications have become increasingly popular, making it important to address their communication needs, where, one of the needs is group communication. In this paper, we consider the applications in which it is at any given time possible to divide its users into groups. The group membership changes over time and the group division is unrelated to the physical proximity. As a way of enabling the group communication in distributed interactive applications we choose application layer multicast. We use simulation to evaluate several dynamic algorithms for managing overlay multicast trees. They are compared with respect to four metrics that can be relevant for a distributed interactive application. These are total tree cost, diameter, reconfiguration time and stability. We demonstrate algorithms that perform well for these metrics although they do not consider all users during reconfiguration.},
	isbn = {978-0-7695-3000-0},
	author = {Vik, Knut-Helge and Griwodz, Carsten and Halvorsen, P{\r a}l},
	editor = {Christensen, Ken and Frank, Matthias}
}
@inproceedings {Simula.ND.43,
	title = {Implementation and Evaluation of Late Data Choice for TCP in Linux},
	journal = {IEEE International Symposium on Multimedia (ISM2007)},
	year = {2007},
	month = {December},
	pages = {221 - 228},
	publisher = {IEEE Computer Society},
	type = {Workshop},
	address = {10662 Los Vaqueros Circle, P.O. Box 3014, Los Alamitos, CA 90720-1314},
	abstract = {Real-time delivery of time-dependent data over the Internet is challenging. UDP has often been used to transport data in a timely manner, but its lack of congestion control is often criticized. This criticism is a reason that the vast majority of applications today use TCP. The downside of this is that TCP has problems with the timely delivery of data. A transport protocol that adds congestion control to an otherwise UDP-like behaviour is DCCP. For this protocol , {{\"\i}t late data choice} (LDC)\~\cite{lai++2005} has been proposed to allow adaptive applications control over data packets up to the actual transmission time. We find, however, that application developers appreciate other TCP features as well, such as its reliability. We have therefore implemented and tested the LDC ideas for TCP. It allows the application to modify or drop packets that have been handed to TCP until they are actually transmitted to the network. This is achieved with a shared packet ring and indexes to hold the current status. Our experiments show that we can send more useful data with LDC than without in a streaming scenario. We can therefore claim that we achieve a better utilization of the throughput, giving u s a higher \textit{goodput} with LDC than without.},
	isbn = {ISBN 0-7695-3058-3},
	author = {Birkedal, Erlend and Griwodz, Carsten and Halvorsen, P{\r a}l}
}
@inproceedings {Simula.ND.35,
	title = {Latency Evaluation of Networking Mechanisms for Game Traffic},
	journal = {Network \& System Support for Games (NetGames 2007)},
	year = {2007},
	pages = {129-134},
	publisher = {ACM},
	type = {Annual},
	abstract = {Large improvements in computer technology allow thousands of users to concurrently interact in a virtual game. Due to this development, the body of work analyzing game traffic has grown considerably in the recent past. However, little work has been done to examine and compare networking techniques with respect to meeting the stringent latency requirements that are common for networked games. Most interactive games need response times between 100 and 1000 ms depending on the game genre. In this paper, we evaluate different techniques for delivering packets in a timely manner. In particular, we compare existing user-space middleware running on top of UDP and reliable, fair transport protocols like TCP and SCTP. In addition, we evaluate some "low latency" extensions to TCP, SCTP and one of the middleware platforms. We present results concerning packet latency and bandwidth requirements for the different approaches.},
	isbn = {ISBN 978-0-9804460-0-5},
	author = {Harcsik, Szabolcs and Petlund, Andreas and Griwodz, Carsten and Halvorsen, P{\r a}l},
	editor = {Armitage, Grenville}
}
@inproceedings {Simula.ND.51,
	title = {Latency Reduction in Massively Multi-Player Online Games by Partial Migration of Game State},
	journal = {Second International Conference on Internet Technologies and Applications},
	year = {2007},
	month = {September},
	pages = {153-163},
	publisher = {Centre for Applied Internet Research (CAIR)},
	type = {Conference},
	address = {University of Wales, NEWI, Wrexham, UK.},
	abstract = {With the increasing popularity of massively multi-player online games (MMOGs), developers are continually forced to deal with the conflicting requirements of supporting a large number of concurrent users, while simultaneously providing low latency. As a result, a common way of distributing load is by dividing the virtual environment into logical regions. Geographically coupled users in such regions can be distinguished by analyzing IP addresses, RTTs or similar. This paper proposes the architecture for a decentralized middleware capable of utilizing such information, with the intent of decreasing the overall latency for the majority of users in that region. The latency reduction is accomplished by migrating a game region to a server closer in locality to the users, thereby lowering the response time of remote procedure calls. Due to the characteristics of MMOGs, the middleware implements a distributed name service, made possible by activating the system from a single node in the system.},
	isbn = {978-0-946881-54-3},
	author = {Beskow, Paul and Halvorsen, P{\r a}l and Griwodz, Carsten},
	editor = {Denise Oram Vic {Grout} and Picking, Rich}
}
@inproceedings {Simula.ND.36,
	title = {Transparent Protocol Translation for Streaming},
	journal = {ACM International Multimedia Conference (ACM MM)},
	year = {2007},
	note = {(short paper) {\textcopyright} ACM, (2007). This is the author{\textquoteright}s version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in Proceedings of the 15th international conference on Multimedia (2007), http://doi.acm.org/10.1145/1291233.1291407},
	month = {September},
	pages = {771-774},
	publisher = {ACM},
	type = {Annual},
	abstract = {The transport of streaming media data over TCP is hindered by TCP{\textquoteright}s probing behavior that results in the rapid reduction and slow recovery of the packet rates. On the other side, UDP has been criticized for being unfair against TCP connections, and it is therefore often blocked out in the access networks. In this paper, we try to benefit from a combined approach using a proxy that transparently performs transport protocol translation. We translate HTTP requests by the client transparently into RTSP requests, and translate the corresponding RTP/UDP/AVP stream into the corresponding HTTP response. This enables the server to use UDP on the server side and TCP on the client side. This is beneficial for the server side that scales to a higher load when it doesn{\textquoteright}t have to deal with TCP. On the client side, streaming over TCP has the advantage that connections can be established from the client side, and data streams are passed through firewalls. Preliminary tests demonstrate that our protocol translation delivers a smoother stream compared to HTTP-streaming where the TCP bandwidth oscillates heavily.},
	isbn = {978-1-59593-702-5},
	author = {Espeland, H{\r a}vard and Carl Henrik {Lunde} and H{\r a}kon Kvale {Stensland} and Griwodz, Carsten and Halvorsen, P{\r a}l},
	editor = {Lienhart, Rainer and Anand R. {Prasad}}
}
@inproceedings {Simula.ND.16,
	title = {Workload Characterization for News-on-Demand Streaming Services},
	journal = {International Performance Computing and Communications Conference (IPCCC)},
	year = {2007},
	month = {April},
	pages = {314-323},
	publisher = {IEEE},
	type = {Annual},
	abstract = {This paper focuses on design issues for multimedia distribution architectures and the impact workload characteristics have on architecture design. Our contribution is an analysis of server load and user behavior in a News-on-Demand environment, with focus on access patterns, popularity modeling, and the formation of traffic peaks. Finally, we evaluate an existing synthetic workload generator, MediSyn, and suggest some enhancements which will improve its suitability for News-on-Demand workload modeling.},
	isbn = {1-4244-1138-6},
	author = {Frank Trethan {Johnsen} and Hafs{\o}e, Trude and Griwodz, Carsten and Halvorsen, P{\r a}l}
}
@inproceedings {Vik.2006.1,
	title = {Applicability of Group Communication for Increased Scalability in MMOGs},
	journal = {Network \& System Support for Games (NetGames 2006)},
	year = {2006},
	month = {October},
	pages = {1-12},
	publisher = {ACM Press},
	type = {Annual},
	edition = {Fifth},
	abstract = {Massive multiplayer online games (MMOGs) are today the driving factor for the development of distributed interactive applications, and they are increasing in size and complexity. Even a small MMOG supports thousands of players, the biggest support hundreds of thousands of concurrent players. Since they are typically built as strict client-server systems, they suffer from the inherent scalability problem of the architecture. Computing power and bandwidth limitations close to the server limit the possible number of players. Also, the latency of communication between players through the server will be higher than using direct communication. In the paper, we address these issues and investigate improvement options. A typical MMOG consists of a virtual world with a concept of time and space that is similar to the real world. In it, players are represented by avatars. Only subsets of these avatars interact with each other at any given time. This allows us to divide them into groups, and communication among group members becomes a multi-party communication problem. Thus, to reduce resource consumption, we compare the performance of several algorithms for group communication with the current central server approach. We use overlay multicast as the means of providing group communication, and research algorithms for creating shortest path trees, spanning trees, delay-bounded spanning trees and, more specific, applying Steiner tree heuristics. Our experimental results indicate that different approaches are useful to reduce resource consumption while achieving a good perceived quality under varying conditions, such as frequent changes in group membership and the demand for low latency.},
	isbn = {1-59593-589-4},
	author = {Vik, Knut-Helge and Griwodz, Carsten and Halvorsen, P{\r a}l},
	editor = {Adrian David {Cheok} and Ishibashi, Yutaka and Natkin, Stephane and Yasumoto, Keiichi}
}
@inproceedings {Griwodz.2006.3,
	title = {Caching of Interactive Multiple Choice MPEG-4 Presentations},
	journal = {International Workshop on Multimedia Systems and Networking (WMSN 2006)},
	year = {2006},
	note = {In proceedings of IEEE International Performance Computing and Communications Conference (IPCCC 2006)},
	month = {April},
	pages = {659-666},
	publisher = {IEEE},
	type = {Annual},
	edition = {25th},
	isbn = {1-4244-0198-4},
	author = {Griwodz, Carsten and Frank Trethan {Johnsen} and Rekkedal, Simen and Halvorsen, P{\r a}l},
	editor = {Hassanein, Hossam and Golden G. {Richards, III}}
}
@inproceedings {Pedersen.2006.1,
	title = {Considerations for SCTP Retransmission Delays for Thin Streams},
	journal = {Local Computer Networks (LCN 2006)},
	year = {2006},
	note = {(best paper award)},
	month = {Nov},
	pages = {135 - 142},
	publisher = {IEEE},
	type = {Annual},
	abstract = {The popularity of distributed interactive applications has exploded in the last few years. For example, massive multi-player online games have become a fast growing, multi-million industry with a very high user mass supporting hundreds or thousands of concurrent players. Today, such games are usually client-server applications that use TCP for time-dependent communication. Similar multimedia applications also choose TCP frequently. Very thin data streams are sent over each of these TCP connections, which means that they consume very little bandwidth. TCP has several shortcomings with respect to the latency requirements of such thin streams because of its retransmission handling. An alternative to TCP may be SCTP which was developed to answer the requirements for signaling transport. SCTP has subsequently also been considered more appropriate than TCP for congestion controlled streaming of other time-dependent data. Important reasons are its maintenance of packet boundaries and partial reliability. In this paper, we evaluate the performance of the Linux SCTP implementation for thin streams. Like others before, we identify latency challenges. We also propose some enhancements for reducing the latency compared to the original Linux implementation. We argue for separate handling of thin and thick data streams in SCTP.},
	isbn = {1-4244-0419-3},
	author = {Pedersen, Jon and Griwodz, Carsten and Halvorsen, P{\r a}l},
	editor = {Christensen, Ken and Frank, Matthias}
}
@inproceedings {Palant.2006.2,
	title = {Consistency Requirements in Multiplayer Online Games},
	journal = {Network \& System Support for Games (NetGames 2006)},
	year = {2006},
	month = {October},
	pages = {1-4},
	publisher = {ACM Press},
	type = {Workshop},
	abstract = {Multi-player online games are becoming increasingly popular as broadband internet connections replace the old modems. However, while available bandwidth grows steadily according to Moore{\textquoteright}s law, the latency of the internet connections remains almost constant, making it difficult to maintain a consistent game state over a large number of clients that have to be synchronized with each other and with the server(s). This paper introduces a possible solution to the problem by defining the necessary level of consistency through user{\textquoteright}s perception of the game. While the resulting set of requirements is somewhat difficult to formalize, it is not too restrictive and leaves many options open, some of which are discussed here. Ideally a game where all the requirements are met will appear like a local game to the user.},
	isbn = {1-59593-589-4},
	author = {Palant, Wladimir and Griwodz, Carsten and Halvorsen, P{\r a}l},
	editor = {Adrian David {Cheok} and Ishibashi, Yutaka and Natkin, Stephane and Yasumoto, Keiichi}
}
@inproceedings {Palant.2006.1,
	title = {Evaluating Dead Reckoning Variations With a Multi-Player Game Simulator},
	journal = {Network and Operating System Support for Digital Audio and Video (NOSSDAV 2006)},
	year = {2006},
	pages = {20-25},
	publisher = {ACM Press},
	type = {Annual},
	abstract = {One of the most difficult tasks when creating an online multi-player game is to provide the players with a consistent view of the virtual world despite the network delays. Most current games use prediction algorithms to achieve this, but usually it does not go beyond applying the DIS dead reckoning algorithm proposed in the mid-90s. In this paper we introduce a simulator called GLS that allows us to evaluate different aspects of DIS and its variations. We examine the impact of prediction and clock synchronization on game consistency. We also evaluate the convergence algorithm we introduce here. Furthermore we look into ways for compensating increasing delays to keep the player{\textquoteright}s view of the game state sufficiently consistent with other players.},
	isbn = {1-59593-285-2},
	author = {Palant, Wladimir and Griwodz, Carsten and Halvorsen, P{\r a}l},
	editor = {Brian Neil {Levine} and Claypool, Mark}
}
@inproceedings {Griwodz.2006.1,
	title = {The Fun of Using TCP for an MMORPG},
	journal = {Network and Operating System Support for Digital Audio and Video (NOSSDAV 2006)},
	year = {2006},
	note = {received the best paper award},
	month = {May},
	pages = {1-7},
	publisher = {ACM Press},
	type = {Annual},
	abstract = {Massive multi-player online games have become a popular, fast growing, multi-million industry with a very high user mass supporting hundreds or thousands of concurrent players. In many cases, these games are centralized and every player communicates with the central server through a time-critical unicast event stream. Funcom{\textquoteright}s Anarchy Online is one of these; it is based on TCP. We find that its kind of traffic has some interesting properties that inspire changes to protocol or architecture. In these game streams, using TCP is not TCP-friendly, using TCP does not have to be slower than using UDP, and only repeated timeouts ruin game experience. Improving the latter in the sender implementation does not impose any remarkable penalty on the network. Alternatively, a proxy architecture for multiplexing could save about 40\% resources at the server, allow congestion control to work and also reduce the lag of the game.},
	isbn = {1-59593-285-2},
	author = {Griwodz, Carsten and Halvorsen, P{\r a}l},
	editor = {Brian Neil {Levine} and Claypool, Mark}
}
@inproceedings {Palant.2006.3,
	title = {GLS: Simulator for Online Multi-Player Games},
	journal = {ACM Multimedia (MM 2006)},
	year = {2006},
	month = {October},
	pages = {805-806},
	publisher = {ACM Press},
	type = {Conference},
	abstract = {One of the most difficult tasks when creating an online multi-player game is to provide the players with a consistent view of the virtual world despite the network delays. Most current games use prediction algorithms to achieve this, however measuring the effect of different approaches is difficult. To solve this problem we introduce a simulator called GLS that gives us a fully controlled environment and allows large-scale experiments to evaluate different aspects of the algorithms.},
	isbn = {1-59593-498-7},
	author = {Palant, Wladimir and Griwodz, Carsten and Halvorsen, P{\r a}l},
	editor = {Mase, Kenji}
}
@inproceedings {Griwodz.2006.2,
	title = {Multicast Tree Reconfiguration in Distributed Interactive Applications},
	journal = {Networking Issues in Multimedia Entertainment (NIME 2006)},
	year = {2006},
	month = {Januar},
	pages = {1219-1223},
	publisher = {IEEE},
	type = {Workshop},
	abstract = {Communication in highly interactive distributed applications, such as massive multiplayer online games, can often be performed efficiently using multicast, i.e., application level multicast. However, in applications with a very dynamic group management, the multicast tree will have frequent changes, and in applications that have stringent latency requirement, this operation needs to be fast. Current multicast approaches either have no notion of reconfiguration, they do not care about tree reconstruction latency or wrongly assume that this is a fast, atomic operation. In this paper, we have focused on dynamic reconfiguration and have tested different ways for a node to join a tree. Our results show that this is an important issue for the class of highly interactive distributed applications.},
	isbn = {1-4244-0086-4},
	author = {Griwodz, Carsten and Vik, Knut-Helge and Halvorsen, P{\r a}l},
	editor = {Roccetti, Marco and Pau, Giovanni and El-Rhalibi, Abdennour}
}
@inproceedings {Halvorsen.2006.1,
	title = {Programmable Subsystems: a Traffic Shaping \& Packet Prioritizing Case Study},
	journal = {International Network Conference (INC 2006)},
	year = {2006},
	month = {July},
	pages = {97-104},
	publisher = {University of Plymouth},
	type = {Conference},
	abstract = {Due to a faster speed increase of networks than processors, we have today a trend towards the distribution of functionality and workload for network processing on several processing units. For this purpose, network processors are being developed which are special processor architectures aimed for demanding networking tasks such as backbone routing and switching. In this paper, we investigate the possibility of improving the scalability of intermediate nodes by offloading the packet processing workload on the host, and in particular, we present a traffic shaper and packet prioritizer implemented on the Intel IXP2400.},
	isbn = {1-84102-157-1},
	author = {Halvorsen, P{\r a}l and {\O}ystein Yri {Sunde} and Petlund, Andreas and Griwodz, Carsten},
	editor = {Furnell, Steven and Dowland, Paul}
}
@inproceedings {Majewski.2006.1,
	title = {Translating Latency Requirements Into Resource Requirements for Game Traffic},
	journal = {International Network Conference (INC 2006)},
	year = {2006},
	month = {July},
	pages = {113-120},
	publisher = {University of Plymouth},
	type = {Conference},
	abstract = {Networked multi-player games constitute a demanding class of interactive distributed multimedia applications with very high commercial relevance. As such, they attract a growing number of researchers in multimedia networking. Most games use a client-server architecture, mainly to prevent cheating. By analyzing the traffic of such games, we confirm that individual client-server flows consume relatively little bandwidth. Thus latency, rather than bandwidth, is the critical parameter when provisioning this class of applications. In order for commercial game services to ensure low-latency operation, resource reservation must be explored. In this paper, we investigate options for a DiffServ-style reservation on part of the path between a game server and sets of clients. We show how a token bucket shaper can be parameterized based on a target end-to-end latency, and discuss the implications for a network infrastructure. We use the shaper to quantify the burstiness of game traffic and the correlation between individual flows, with a view to the limitations this imposes on resource reservation for aggregate (multiplexed) flows.},
	isbn = {1-84102-157-1},
	author = {Majewski, Chris and Griwodz, Carsten and Halvorsen, P{\r a}l},
	editor = {Furnell, Steven and Dowland, Paul}
}
@inproceedings {Halvorsen.2005.1,
	title = {Assessment of Data Path Implementations for Download and Streaming},
	journal = {International Conference on Distributed Multimedia Systems (DMS)},
	year = {2005},
	month = {september},
	pages = {228-233},
	publisher = {Knowledge Systems Institute},
	type = {Conference},
	address = {3420 Main Street, Skokie, IL 60076, USA},
	abstract = {Distributed multimedia streaming systems are increasingly popular due to technological advances, and numerous streaming services are available today. On servers or proxy caches, there is a huge scaling challenge in supporting thousands of concurrent users that request delivery of high-rate, time-dependent data like audio and video, because this requires transfers of large amounts of data through several sub-systems within a streaming node. Since the speed increase for memory accesses does not follow suite with the CPU speed, copy operations can be a severe limiting factor on the streaming performance of off-the-shelf operating systems, which still have only limited support for data paths that have been optimized for streaming despite previous research proposals. We observe furthermore that while CPU speed continues to increase, system call overhead has grown as well, adding to the cost of data movement. In this paper, we therefore revisit the data movement problem and provide a comprehensive evaluation of possible streaming data I/O paths in Linux 2.6 kernel. We have implemented and evaluated enhanced mechanisms and show how to provide support for more ef cient memory usage and reduction of user/kernel space switches for streaming applications.},
	isbn = {1-891706-17-9},
	author = {Halvorsen, P{\r a}l and Tom Anders {Dalseng} and Griwodz, Carsten},
	editor = {Chang, Shi-Kuo and Arndt, Timothy}
}
@inproceedings {Thomas.2005.2,
	title = {Middleware Services for Information Sharing in Mobile Ad-Hoc Networks},
	journal = {Broadband Satellite Communication Systems and the Challenges of Mobility},
	year = {2005},
	pages = {225-236},
	publisher = {Springer Publishing Company},
	type = {Workshop},
	author = {Plagemann, Thomas and Andersson, Jon and Ovidiu Valentin {Drugan} and Goebel, Vera and Griwodz, Carsten and Halvorsen, P{\r a}l and Munthe-Kaas, Ellen and Puzar, Matija and Norun Christine {Sanderson} and Skjelsvik, Katrine},
	editor = {Gayraud, T. and Mazella, M. and Fernandes, F.P. and Monteiro, E. and Orvalho, J.G.d.M.}
}
@inproceedings {Oyvind.2005.1,
	title = {Offloading Multimedia Proxies Using Network Processors},
	journal = {International Network Conference (INC)},
	year = {2005},
	month = {july},
	pages = {113-120},
	publisher = {University of Plymouth},
	type = {1},
	abstract = {In this paper, we present a system that aims at of oading multimedia proxies using network processing technology for applications like media-on-demand and distributed on-line games. In particular, we have designed, implemented and evaluated a proof-of-concept prototype on the Intel IXP1200 network processor. Our results show that the prototype succeeds in of oading the host machine as no data packets have to be processed by the host CPU, and the prototype is able to perform application layer forwarding using only a fraction of the cycles compared to a traditional architecture, where all packets are processed by the host CPU.},
	isbn = {960-7475-32-1},
	author = {Hvamstad, {\O}yvind and Griwodz, Carsten and Halvorsen, P{\r a}l},
	editor = {S. M. {Furnell} and P. S. {Dowland} and Kormentzas, G.}
}
@inproceedings {Amundsen.2005.1,
	title = {QoS-Aware Mobile Middleware for Video Streaming},
	journal = {31st EUROMICRO Conference on Software Engineering and Advanced Applications (SEAA), Portugal August 30-September 3},
	year = {2005},
	month = {September},
	pages = {54-61},
	publisher = {IEEE Computer Society},
	type = {1},
	author = {Sten Lundesgaar {Amundsen} and Lund, Ketil and Griwodz, Carsten and Halvorsen, P{\r a}l}
}
@article {halvorsen-dsonline-2004a,
	title = {Storage System Support for Continuous-Media Applications, Part 1: Requirements and Single-Disk Issues},
	journal = {IEEE Distributed Systems Online},
	volume = {5},
	number = {1},
	year = {2004},
	month = {January},
	author = {Halvorsen, P{\r a}l and Griwodz, Carsten and Goebel, Vera and Lund, Ketil and Plagemann, Thomas and Walpole, Jonathan}
}
@article {halvorsen-dsonline-2004b,
	title = {Storage System Support for Continuous-Media Applications, Part 2: Multiple Disks, Memory, and Integration},
	journal = {IEEE Distributed Systems Online},
	volume = {5},
	number = {2},
	year = {2004},
	month = {February},
	author = {Halvorsen, P{\r a}l and Griwodz, Carsten and Goebel, Vera and Lund, Ketil and Plagemann, Thomas and Walpole, Jonathan}
}
@inproceedings {johnsen-2004,
	title = {Structured Partially Caching Proxies for Mixed Media},
	journal = {Web Content Caching and Distribution: 9th International Workshop},
	year = {2004},
	month = {oct},
	pages = {144-153},
	publisher = {Springer},
	type = {Annual},
	abstract = {Proceedings of the International Workshop on Web Content Caching and Distribution (WCW)},
	isbn = {3-540-23516-7},
	author = {Frank Trethan {Johnsen} and Griwodz, Carsten and Halvorsen, P{\r a}l},
	editor = {Chi, Chi-Hung and van Steen, Maarten and Craig E. {Wills}}
}
@inproceedings {Griwodz.2004.2,
	title = {Translating Scalable Video Streams From Wide-Area to Access Networks},
	journal = {Proceedings of the International Network Conference (INC{\textquoteright}04)},
	year = {2004},
	month = {July},
	pages = {102-110},
	publisher = {Network Research Group},
	type = {1},
	address = {University of Plymouth, Drake Circus, Plymouth PL4 8AA, UK},
	author = {Griwodz, Carsten and Fiksdal, Steffen and Halvorsen, P{\r a}l},
	editor = {Steven M. {Furnell} and Paul S. {Dowland}}
}
@article {Griwodz.2004.1,
	title = {Translating Scalable Video Streams From Wide-Area to Access Networks},
	journal = {Campus-Wide Information Systems},
	volume = {21},
	number = {5},
	year = {2004},
	pages = {205-210},
	author = {Griwodz, Carsten and Fiksdal, Steffen and Halvorsen, P{\r a}l}
}
@article {halvorsen2003,
	title = {Improving the I/O Performance of Intermediate Multimedia Storage Nodes},
	journal = {ACM/Springer Multimedia Systems},
	volume = {9},
	number = {1},
	year = {2003},
	month = {jul},
	pages = {56-67},
	author = {Halvorsen, P{\r a}l and Plagemann, Thomas and Goebel, Vera}
}
@techreport {ND.7.Halorsen.2003,
	title = {Storage System Support for Multimedia Applications},
	number = {307},
	year = {2003},
	note = {ISBN 82-7368-259-5},
	month = {June},
	publisher = {Department of Informatics, University of Oslo},
	author = {Halvorsen, P{\r a}l and Griwodz, Carsten and Lund, Ketil and Goebel, Vera and Plagemann, Thomas}
}
@inproceedings {plagemann03,
	title = {Towards Middleware Services for Ad-Hoc Network Applications},
	journal = {Proceedings of the Workshop on Future Trends of Distributed Computing Systems (FTDCS)},
	year = {2003},
	month = {may},
	pages = {249-257},
	type = {1},
	author = {Plagemann, Thomas and Goebel, Vera and Griwodz, Carsten and Halvorsen, P{\r a}l}
}
@inproceedings {plagemann03b,
	title = {Towards Scalable and Affordable Content Distribution Services},
	journal = {Proceedings of the International Conference on Telecommunications (ConTEL)},
	year = {2003},
	month = {jun},
	pages = {307-314},
	publisher = {IEEE},
	type = {Annual},
	isbn = {953-184-052-0},
	author = {Plagemann, Thomas and Goebel, Vera and Griwodz, Carsten and Halvorsen, P{\r a}l and Mathey, Laurent and Zink, Michael},
	editor = {Matija{\v s}evi{\'c}, Maja and Igor S. {Pandzic}}
}
@inproceedings {halvorsen02,
	title = {How to Minimize Transport Protocol Processing: Implementation and Evaluation of Network Level Framing},
	journal = {conf\_mnsa},
	year = {2002},
	month = {jul},
	pages = {149-155},
	type = {1},
	author = {Halvorsen, P{\r a}l and Plagemann, Thomas and Goebel, Vera}
}
@inproceedings {halvorsen01,
	title = {Integrated Error Management for Media-on-Demand Services},
	journal = {Proceedings of the Joint Conference of the IEEE Computer and Communications Societies (INFOCOM)},
	year = {2001},
	month = {apr},
	pages = {621-630},
	publisher = {IEEE Press},
	type = {1},
	author = {Halvorsen, P{\r a}l and Plagemann, Thomas and Goebel, Vera}
}
@inproceedings {ND.5.Lund.2000,
	title = {Requirements Analysis and Design for a Flexible Learning-on-Demand System},
	journal = {World Conference on Integrated Design and Process Technology (IDPT 1999)},
	year = {2000},
	publisher = {SDPS},
	type = {1},
	address = {Dallas, TX, USA},
	author = {Lund, Ketil and Halvorsen, P{\r a}l and Goebel, Vera and Plagemann, Thomas}
}
@inproceedings {Halvorsen.1999.1,
	title = {ConfMan: Integrated WWW and DBS Support for Conference Organization},
	journal = {Poster Proceedings of The Eighth International World Wide Web Conference (WWW{\textquoteright}8)},
	year = {1999},
	month = {May},
	publisher = {Elsevier},
	type = {1},
	author = {Halvorsen, P{\r a}l and Lund, Ketil and Goebel, Vera and Plagemann, Thomas and Preuss, Thomas and Koenig, Harmut}
}
@inproceedings {ND.5.Goebel.1998,
	title = {Towards QoS Support in Multimedia Database Management Systems (Poster)},
	journal = {The 6th ACM Multimedia Conference 98},
	year = {1998},
	month = {September,},
	pages = {52-54},
	publisher = {ACM},
	type = {1},
	address = {Bristol, UK},
	author = {Goebel, Vera and Halvorsen, P{\r a}l and Lund, Ketil and Mirzadeh, N. and Plagemann, Thomas}
}
