A Novel Approach to Robust Background Subtraction

  • Walter Izquierdo Guerra
  • Edel García-Reyes
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5856)

Abstract

Nowadays, background model does not have any robust solution and constitutes one of the main problems in surveillance systems. Researchers work in several approaches in order to get better background pixel models. This is a previous step to apply the background subtraction technique and results are not as good as people expect. We propose a novel approach to the background subtraction technique without a strong dependence of the background pixel model. We compare our algorithm versus Wallflower algorithm [1]. We use the standards deviation of the difference as an independent initial parameter to reach an adjusted threshold for every moment. This solution is more efficient computationally than the wallflower approach.

Keywords

Gaussian Mixture Model Background Subtraction Current Image Illumination Change Foreground Pixel 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Walter Izquierdo Guerra
    • 1
  • Edel García-Reyes
    • 1
  1. 1.Advanced Technologies Application Center (CENATAV)La HabanaCuba

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