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A method for mixed states texture segmentation with simultaneous parameter estimation

delete2011-11-01
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PRE
AI
A
Agustín Mailing *
B
Bruno Cernuschi-Frías
DOI:10.1016/j.patrec.2011.07.022delete
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Abstract

Abstract

En 中文
In this work a method for mixed-state model motion texture segmentation and parameter estimation is presented. We use the Expectation Maximization algorithm for mixture parameter estimation, introducing the Gibbs distribution for moving points, excluding zero discrete component associated with no motion regions. We use then the a posteriori probabilities to generate an alternative field to segment the textures according to its statistical parameters. (C) 2011 Elsevier B.V. All rights reserved.
Keywords:
Motion textures
Segmentation
Expectation Maximization
Pseudo-likelihood
Markov Random Fields

Journal

Pattern Recognition Letters cover
Pattern Recognition Letters
IF:
3.3
Papers:
8.0K
Citations:
1.6W

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No organization information available
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