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Proceedings Paper

Clustering methods for video browsing and annotation
Author(s): Di Zhong; HongJiang Zhang; Shih-Fu Chang
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Paper Abstract

The large amount of video data makes it a tedious and hard job to browse and annotate them by just fast forward and rewind. Recent works in video parsing provide a foundation for building interactive and content based video browsing systems. In this paper, a generalized top-down hierarchial clustering process, which adopts partition clustering recursively at each level of the hierarchy, is studied and used to build hierarchical views of video shots. With the clustering processes, when a list of video programs or clips is provided, a browsing system can use either key-frame and/or shot features to cluster shots into classes, each of which consists of shots of similar content. After such clustering, each class of shots can be represented by an icon, which can then be displayed at the high levels of a hierarchical browser. As a result, users can know roughly the content of video shots even without moving down to a lower level of the hierarchy.

Paper Details

Date Published: 13 March 1996
PDF: 8 pages
Proc. SPIE 2670, Storage and Retrieval for Still Image and Video Databases IV, (13 March 1996); doi: 10.1117/12.234800
Show Author Affiliations
Di Zhong, National Univ. of Singapore (China)
HongJiang Zhang, National Univ. of Singapore (China)
Shih-Fu Chang, Columbia Univ. (United States)


Published in SPIE Proceedings Vol. 2670:
Storage and Retrieval for Still Image and Video Databases IV
Ishwar K. Sethi; Ramesh C. Jain, Editor(s)

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