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Proceedings Paper

Video classification in user profile generation for personalized broadcast services
Author(s): Ying Li; C.-C. Jay Kuo
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Paper Abstract

Automatic generation of user profiles, as specified in the MPEG-7 user preference description scheme, for personized broadcast services is investigated in this work. Our research has focused on categorization of user-favored video into different semantically meaningful classes. This knowledge is then used in media filtering guidance and user preferred AV content selection. Several visual and motion features are extracted from source video sequences, such as the number of intra-coded macroblocks, the macroblock motion information, temporal variances and shot activity histograms, for the classification purposes. Moreover, to further improve the accuracy of classification results, a 'fuzzy nearest prototype classifier' is applied in this work. It is shown by experimental results that the proposed classification scheme is efficient and accurate.

Paper Details

Date Published: 29 December 2000
PDF: 12 pages
Proc. SPIE 4310, Visual Communications and Image Processing 2001, (29 December 2000); doi: 10.1117/12.411826
Show Author Affiliations
Ying Li, Univ. of Southern California (United States)
C.-C. Jay Kuo, Univ. of Southern California (United States)

Published in SPIE Proceedings Vol. 4310:
Visual Communications and Image Processing 2001
Bernd Girod; Charles A. Bouman; Eckehard G. Steinbach, Editor(s)

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