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» Using High-Level Semantic Features in Video Retrieval
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CVPR
2005
IEEE
13 years 10 months ago
Mapping Low-Level Features to High-Level Semantic Concepts in Region-Based Image Retrieval
In this a novel supervised learning method is proposed to map low-level visualfeatures to high-level semantic conceptsfor region-based image retrieval. The contributions of thispa...
Wei Jiang, Kap Luk Chan, Mingjing Li, HongJiang Zh...
TRECVID
2007
13 years 6 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...
CVPR
2008
IEEE
14 years 6 months ago
Utilizing semantic word similarity measures for video retrieval
This is a high level computer vision paper, which employs concepts from Natural Language Understanding in solving the video retrieval problem. Our main contribution is the utiliza...
Yusuf Aytar, Mubarak Shah, Jiebo Luo
WWW
2006
ACM
14 years 5 months ago
An audio/video analysis mechanism for web indexing
The high availability of video streams is making necessary mechanisms for indexing such contents in the Web world. In this paper we focus on news programs and we propose a mechani...
Marco Furini, Marco Aragone
TRECVID
2008
13 years 6 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...