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Mixture Models Based Background Subtraction for Video Surveillance Applications

  • Chris Poppe
  • Gaëtan Martens
  • Peter Lambert
  • Rik Van de Walle
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4673)

Abstract

Background subtraction is a method commonly used to segment objects of interest in image sequences. By comparing new frames to a background model, regions of interest can be found. To cope with highly dynamic and complex environments, a mixture of several models has been proposed in the literature. This paper proposes a novel background subtraction technique based on the popular Mixture of Gaussian Models technique. Moreover edge-based image segmentation is used to improve the results of the proposed technique. Experimental analysis shows that our system outperforms the standard system both in processing speed and detection accuracy.

Keywords

Object Detection Mixture of Gaussian Models Video Surveillance 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Chris Poppe
    • 1
  • Gaëtan Martens
    • 1
  • Peter Lambert
    • 1
  • Rik Van de Walle
    • 1
  1. 1.Ghent University - IBBT, Department of Electronics and Information Systems - Multimedia Lab, Gaston Crommenlaan 8, B-9050 Ledeberg-GhentBelgium

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