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Proceedings Paper

Background subtraction based on nonparametric Bayesian estimation
Author(s): Yan He; Donghui Wang; Miaoliang Zhu
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Paper Abstract

Background subtraction, the task of separating foreground pixels from background pixels in a video, is an important step in video processing. Comparing with the parametric background modeling methods, nonparametric methods use a model selection criterion to choose the right number of components for each pixel online. We model the background subtraction problem with the Dirichlet process mixture, which constantly adapts both the parameters and the number of components of the mixture to the scene.

Paper Details

Date Published: 8 July 2011
PDF: 5 pages
Proc. SPIE 8009, Third International Conference on Digital Image Processing (ICDIP 2011), 80090G (8 July 2011); doi: 10.1117/12.896509
Show Author Affiliations
Yan He, Zhejiang Univ. (China)
Zhejiang Financial College (China)
Donghui Wang, Zhejiang Univ. (China)
Miaoliang Zhu, Zhejiang Univ. (China)

Published in SPIE Proceedings Vol. 8009:
Third International Conference on Digital Image Processing (ICDIP 2011)
Ting Zhang, Editor(s)

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