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Proceedings Paper

Fast coarse-to-fine video retrieval via shot-level statistics
Author(s): Yu-Hsuan Ho; Chia-Wen Lin; Jing-Fung Chen; Hong-Yuan Mark Liao
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Paper Abstract

We propose a fast coarse-to-fine video retrieval scheme using shot-level spatio-temporal statistics. The proposed scheme consists of a two-step coarse search and a fine search. At the coarse-search stage, the shot-level motion and color distributions are computed as the spatio-temporal features for shot matching. The first-pass coarse search uses the shot-level global statistics to cut down the size of the search space drastically. By adding an adjacent shot of the first query shot, the second-pass coarse-search introduces the "causality" relation between two consecutive shots to improve the search accuracy. As a result, the final fine-search step based on local color features of key-frames of the query shot is performed to further refine the search result. Experimental results show that the proposed methods can achieve good retrieval performance with a much reduced complexity compared to single-pass methods.

Paper Details

Date Published: 24 June 2005
PDF: 12 pages
Proc. SPIE 5960, Visual Communications and Image Processing 2005, 59600Q (24 June 2005); doi: 10.1117/12.631379
Show Author Affiliations
Yu-Hsuan Ho, National Chung Cheng Univ. (Taiwan)
Chia-Wen Lin, National Chung Cheng Univ. (Taiwan)
Jing-Fung Chen, Institute of Information Science, Academia Sinica (Taiwan)
Hong-Yuan Mark Liao, Institute of Information Science, Academia Sinica (Taiwan)

Published in SPIE Proceedings Vol. 5960:
Visual Communications and Image Processing 2005
Shipeng Li; Fernando Pereira; Heung-Yeung Shum; Andrew G. Tescher, Editor(s)

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