@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.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.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}}
}
@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}
}
