@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}
}
@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 {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 {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}
}
@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}
}
