Paper
13 March 1996 Clustering methods for video browsing and annotation
Author Affiliations +
Proceedings Volume 2670, Storage and Retrieval for Still Image and Video Databases IV; (1996) https://doi.org/10.1117/12.234800
Event: Electronic Imaging: Science and Technology, 1996, San Jose, CA, United States
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.
© (1996) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Di Zhong, HongJiang Zhang, and Shih-Fu Chang "Clustering methods for video browsing and annotation", Proc. SPIE 2670, Storage and Retrieval for Still Image and Video Databases IV, (13 March 1996); https://doi.org/10.1117/12.234800
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CITATIONS
Cited by 165 scholarly publications and 1 patent.
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KEYWORDS
Video

Visualization

Video processing

RGB color model

Databases

Image retrieval

Video compression

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