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Proceedings Paper

Discovering video structure using the pseudosemantic trace
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Paper Abstract

In this paper, we describe a framework of analyzing programs belonging to different TV program genres Hidden Markov Models and pseudo-semantic feature s derived from video shots. Clustering using Gaussian mixture models is used to determine the order of the modes. Results for initial genre classification experiments using two simple features derived from video shots are given.

Paper Details

Date Published: 1 January 2001
PDF: 8 pages
Proc. SPIE 4315, Storage and Retrieval for Media Databases 2001, (1 January 2001); doi: 10.1117/12.410970
Show Author Affiliations
Cuneyt M. Taskiran, Purdue Univ. (United States)
Charles A. Bouman, Purdue Univ. (United States)
Edward J. Delp, Purdue Univ. (United States)


Published in SPIE Proceedings Vol. 4315:
Storage and Retrieval for Media Databases 2001
Minerva M. Yeung; Chung-Sheng Li; Rainer W. Lienhart, Editor(s)

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