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학술대회 Video Retrieval Method Using Non-parametric Based Motion Classification
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김낙우, 송호영
International Conference on Image Analysis and Recognition (ICIAR) 2008 (LNCS 5112), v.5112, pp.281-293
08ZT1100, 광가입자망(FTTH)서비스 개발 실험사업, 고재상
In this paper, we propose a novel video retrieval method using non-parametric based motion classification in the shot-based video indexing structure. The proposed system gets the representative frame and motion information from each shot segmented by the shot change detection method, and extracts visual features and non-parametric based motion information from them. Then, we construct a real-time video retrieval system using similarity comparison between these spatio-temporal features. The extraction of non-parametric based motion features, after the normalized motion vectors are created from an MPEG-compressed stream, is effectively fulfilled by discretizing each normalized motion vector into various angle bins, and by considering the mean, variance, and direction of motion vectors in these bins. In addition, we use the edge-based spatial descriptor to extract the visual feature in representative frames. Experimental evidence shows that our algorithm outperforms other video retrieval methods for image indexing and retrieval. To index the feature vectors, we use R*-tree structures. © 2008 Springer-Verlag Berlin Heidelberg.
KSP 제안 키워드
Detection Method, Edge-based, Feature Vector, Image indexing, Indexing and retrieval, Indexing structure, Motion Classification, Motion Vector(MV), Motion information, Non-Parametric, Real-time video