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TRECVID
2007
13 years 8 months ago
ENST/UOB/LU@TRECVID2007 HIGH LEVEL FEATURE EXTRACTION USING 2-LEVEL PIECEWISE GMM
We describe a high level feature extraction system for video. Video sequences are modeled using Gaussian Mixture Models. We have used those models in the past to segment video seq...
George Yazbek, Georges Kfoury, Gabriel Alam, Chafi...
TRECVID
2008
13 years 9 months ago
Glasgow University at TRECVID 2008
In this paper we describe our experiments in the automatic and interactive search tasks of TRECVID 2008. We submitted six runs, five of them are automatic and one is interactive. ...
P. Punitha, Thierry Urruty, Yue Feng, Martin Halve...
TRECVID
2007
13 years 8 months ago
Eurecom at TRECVid 2007: Extraction of High-level Features
In this paper we describe our experiments for the high level features extraction task of TRECVid 2007. Our approach is different than previous submissions in that we have impleme...
Rachid Benmokhtar, Eric Galmar, Benoit Huet
TRECVID
2008
13 years 9 months ago
Learning TRECVID'08 High-Level Features from YouTube
Run No. Run ID Run Description infMAP (%) training on TV08 data 1 IUPR-TV-M SIFT visual words with maximum entropy 6.1 2 IUPR-TV-MF SIFT with maximum entropy, fused with color+tex...
Adrian Ulges, Christian Schulze, Markus Koch, Thom...
CIVR
2006
Springer
139views Image Analysis» more  CIVR 2006»
13 years 11 months ago
Using High-Level Semantic Features in Video Retrieval
Extraction and utilization of high-level semantic features are critical for more effective video retrieval. However, the performance of video retrieval hasn't benefited much d...
Wujie Zheng, Jianmin Li, Zhangzhang Si, Fuzong Lin...