Paper Title:
Research on GMM Background Modeling and its Covariance Estimation
  Abstract

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)
Chapter
Chapter 8: Modeling, Analysis, and Simulation of Manufacturing Processes
Edited by
Wu Fan
Pages
2327-2333
DOI
10.4028/www.scientific.net/AMR.383-390.2327
Citation
Y. C. Zhang, R. M. Zhang, S. J. Song, "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
$32.00
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