Research on GMM Background Modeling and its Covariance Estimation

Abstract:

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This paper analyzes the background modeling mechanism using Gaussian mixture model and the stability /plasticity dilemma in parameters estimation of GMM background model. To solve the slow convergence problem of Gaussian mean and covariance update formula given by Stauffer, a new updating strategy is proposed, which weighs the model adaptability and motion segmentation accuracy. Experiments show that the proposed algorithm improves the accuracy of modal learning and speed of covariance convergence.

Info:

Periodical:

Advanced Materials Research (Volumes 383-390)

Edited by:

Wu Fan

Pages:

2327-2333

DOI:

10.4028/www.scientific.net/AMR.383-390.2327

Citation:

Y. C. Zhang et al., "Research on GMM Background Modeling and its Covariance Estimation", Advanced Materials Research, Vols. 383-390, pp. 2327-2333, 2012

Online since:

November 2011

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Price:

$35.00

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