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Proceedings Paper

Video browsing using clustering and scene transitions on compressed sequences
Author(s): Minerva M. Yeung; Boon-Lock Yeo; Wayne H. Wolf; Bede Liu
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Paper Abstract

This paper describes a new technique for extracting a hierarchical decomposition of a complex video selection for browsing purposes. The technique combines visual and temporal information to capture the important relations within a scene and between scenes in a video, thus allowing the analysis of the underlying story structure with no a priori knowledge of the content. We define a general model of hierarchical scene transition graph, and apply this model in an implementation for browsing. Video shots are first identified and a collection of key frames is used to represent each video segment. These collections are then classified according to gross visual information. A platform is built on which the video is presented as directed graphs to the user, with each category of video shots represented by a node and each edge denotes a temporal relationship between categories. The analysis and processing of video is carried out directly on the compressed videos. Preliminary tests show that the narrative structure of a video selection can be effectively captured using this technique.

Paper Details

Date Published: 14 March 1995
PDF: 15 pages
Proc. SPIE 2417, Multimedia Computing and Networking 1995, (14 March 1995); doi: 10.1117/12.206067
Show Author Affiliations
Minerva M. Yeung, Princeton Univ. (United States)
Boon-Lock Yeo, Princeton Univ. (United States)
Wayne H. Wolf, Princeton Univ. (United States)
Bede Liu, Princeton Univ. (United States)


Published in SPIE Proceedings Vol. 2417:
Multimedia Computing and Networking 1995
Arturo A. Rodriguez; Jacek Maitan, Editor(s)

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