Name
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 |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1109/ICME.2005.1521736 | Amsterdam |
Keywords | Field | DocType |
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 | World Wide Web,Video retrieval,TRECVID,Computer science,Search engine indexing,Semantic learning,Mobile device,Content based retrieval,Multimedia,Semantics,The Internet | Conference |
ISBN | Citations | PageRank |
0-7803-9331-7 | 2 | 0.38 |
References | Authors | |
1 | 8 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Cees G.M. Snoek | 1 | 4068 | 239.71 |
| Dennis Koelma | 2 | 367 | 39.75 |
| Jeroen van Rest | 3 | 20 | 4.46 |
| Nellie Schipper | 4 | 3 | 0.73 |
| Frank J. Seinstra | 5 | 298 | 31.00 |
| Andrew Thean | 6 | 10 | 1.63 |
| Marcel Worring | 7 | 6439 | 384.88 |
| van Rest, J. | 8 | 2 | 0.38 |