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Conference Paper Video Retrieval Method Using Non-parametric Based Motion Classification
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Authors
N.W. Kim, H.Y. Song
Issue Date
2008-06
Citation
International Conference on Image Analysis and Recognition (ICIAR) 2008 (LNCS 5112), v.5112, pp.281-293
Language
English
Type
Conference Paper
DOI
https://dx.doi.org/10.1007/978-3-540-69812-8_28
Project Code
08ZT1100, Experimental Project for FTTH Service Development, Koh Jaisang
Abstract
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 Keywords
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