NDLI: On clustering and retrieval of video shots

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On clustering and retrieval of video shots

Content Provider	ACM Digital Library
Author	Ngo, Chong-Wah Pong, Ting-Chuen Zhang, Hong-Jiang
Abstract	Clustering of video data is an important issue in video abstraction, browsing and retrieval. In this paper, we propose a two-level hierarchical clustering approach by aggregating shots with similar motion and color features. Motion features are computed directly from 2D tensor histograms, while color features are represented by 3D color histograms. Cluster validity analysis is further applied to automatically determine the number of clusters at each level. Video retrieval can then be done directly based on the result of clustering. The proposed approach is found to be useful particularly for sports games, where motion and color are important visual cues when searching and browsing the desired video shots. Since most games involve two teams, clsssification and retrieval of teams becomes an interesting topic. To achieve these goals, nevertheless, an initial as well as critical step is to isolate team players from background regions. Thus, we also introduce approach to segment foreground objects (players) prior to classification and retrieval.
Starting Page	51
Ending Page	60
Page Count	10
File Format	PDF
ISBN	1581133944
DOI	10.1145/500141.500151
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2001-10-01
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Hierarchical clustering Motion and color retrieval Team classification
Content Type	Text
Resource Type	Article

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