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Proceedings Paper

Bayesian approach to segmentation of temporal dynamics in video data
Author(s): Coleen T. Jones; Ken D. Sauer
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Paper Abstract

We present an algorithm for Bayesian estimation of temporally active spatial regions of video sequences. The algorithm improves the effectiveness of conditional replenishment for video compression in many applications which feature a background/foreground format. For the sake of compatibility with prevalent block-type coders, the binaryvalued segmentation is constrained to be constant on square blocks of 8x8 or 16 x 16 pixels. Our approach favors connectivity at two levels of scale. The first is at the individual pixel level, where a Gibbs distribution is used for the active pixels in the binary field of supra-threshold interframe differences. The final segmentation also assigns higher probability to patterns of active blocks which are connected, since in general, macroscopic entities are assumed to be many blocks in size. Demonstrations of the advantage of the Bayesian approach are given through simulations with standard sequences.

Paper Details

Date Published: 1 November 1991
PDF: 12 pages
Proc. SPIE 1605, Visual Communications and Image Processing '91: Visual Communication, (1 November 1991); doi: 10.1117/12.50248
Show Author Affiliations
Coleen T. Jones, U.S. Dept. of Commerce (United States)
Ken D. Sauer, Univ. of Notre Dame (United States)

Published in SPIE Proceedings Vol. 1605:
Visual Communications and Image Processing '91: Visual Communication
Kou-Hu Tzou; Toshio Koga, Editor(s)

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