DocumentCode
2243656
Title
Mediamill: Searching Multimedia Archives Based on Learned Semantics
Author
Snoek, C.G.M. ; Koelma, D.C. ; van Rest, J. ; Schipper, N. ; Seinstra, F.J. ; Thean, A. ; Worring, M.
Author_Institution
MediaMill, Amsterdam
fYear
2005
fDate
6-6 July 2005
Firstpage
1575
Lastpage
1577
Abstract
Video is about to conquer the Internet. Real-time delivery of video content is technically possible to any desktop and mobile device, even with modest connections. The main problem hampering massive (re)usage of video content today is the lack of effective content-based tools that provide semantic access. In this contribution, we discuss systems for both video analysis and video retrieval that facilitate semantic access to video sources. Both systems were evaluated in the 2004 TRECVID benchmark as top performers in their task
Keywords
Internet; content-based retrieval; multimedia computing; video retrieval; 2004 TRECVID benchmark; Internet; MediaMill; content-based tool; mobile device; multimedia archive searching; semantic learning; video retrieval; Airplanes; Cellular neural networks; Humans; Indexing; Internet; NIST; Particle measurements; Performance evaluation; Search engines; Vehicles;
fLanguage
English
Publisher
ieee
Conference_Titel
Multimedia and Expo, 2005. ICME 2005. IEEE International Conference on
Conference_Location
Amsterdam
Print_ISBN
0-7803-9331-7
Type
conf
DOI
10.1109/ICME.2005.1521736
Filename
1521736
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