DocumentCode :
922928
Title :
Clip-based similarity measure for query-dependent clip retrieval and video summarization
Author :
Peng, Yuxin ; Ngo, Chong-Wah
Volume :
16
Issue :
5
fYear :
2006
fDate :
5/1/2006 12:00:00 AM
Firstpage :
612
Lastpage :
627
Abstract :
This paper proposes a new approach and algorithm for the similarity measure of video clips. The similarity is mainly based on two bipartite graph matching algorithms: maximum matching (MM) and optimal matching (OM). MM is able to rapidly filter irrelevant video clips, while OM is capable of ranking the similarity of clips according to visual and granularity factors. We apply the similarity measure for two tasks: retrieval and summarization. In video retrieval, a hierarchical retrieval framework is constructed based on MM and OM. The validity of the framework is theoretically proved and empirically verified on a video database of 21 h. A query-dependent clip segmentation algorithm is also proposed to automatically locate the potential boundaries of clips in videos. In video summarization, a graph-based clustering algorithm, incorporated with the proposed similarity measure, is adopted to detect the highlighted events reported by different newscasts.
Keywords :
image matching; image segmentation; query formulation; video retrieval; bipartite graph matching algorithms; clip-based similarity measure; graph-based clustering algorithm; hierarchical retrieval framework; maximum matching; optimal matching; query-dependent clip retrieval; query-dependent clip segmentation; video retrieval; video summarization; Bipartite graph; Cameras; Clustering algorithms; Computer science; Event detection; Filters; Information retrieval; Layout; Optimal matching; Visual databases; Clip similarity; hierarchical video retrieval; query-based segmentation; summarization;
fLanguage :
English
Journal_Title :
Circuits and Systems for Video Technology, IEEE Transactions on
Publisher :
ieee
ISSN :
1051-8215
Type :
jour
DOI :
10.1109/TCSVT.2006.873157
Filename :
1626302
Link To Document :
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