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A Fuzzy Background Modeling Approach for Motion Detection in Dynamic Backgrounds

  • Zhenjie Zhao
  • Thierry Bouwmans
  • Xuebo Zhang
  • Yongchun Fang
Part of the Communications in Computer and Information Science book series (CCIS, volume 346)

Abstract

Based on Type-2 Fuzzy Gaussian Mixture Model (T2-FGMM) and Markov Random Field (MRF), we propose a novel background modeling method for motion detection in dynamic scenes. The key idea of the proposed approach is the successful introduction of the spatial-temporal constraints into the T2-FGMM by a Bayesian framework. The evaluation results in pixel level demonstrate that the proposed method performs better than the sound Gaussian Mixture Model (GMM) and T2-FGMM in such typical dynamic backgrounds as waving trees and water rippling.

Keywords

T2-FGMM MRF motion detection dynamic backgrounds 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Zhenjie Zhao
    • 1
  • Thierry Bouwmans
    • 2
  • Xuebo Zhang
    • 1
  • Yongchun Fang
    • 1
  1. 1.Institute of Robotics and Automatic Information SystemNankai UniversityChina
  2. 2.Laboratory of Mathematics, Images and ApplicationsUniversity of La RochelleFrance

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