Enhanced Codebook Model for Real-Time Background Subtraction

  • Munir Shah
  • Jeremiah Deng
  • Brendon Woodford
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7064)

Abstract

The CodeBook is one of the popular real-time background models for moving object detection in a video. However, for some of the complex scenes, it does not achieve satisfactory results due to the lack of an automatic parameters estimation mechanism. In this paper, we present an improved CodeBook model, which is robust in sudden illumination changes and quasi-periodic motions. The major contributions of the paper are a robust statistical parameter estimation method, a controlled adaptation procedure, a simple, but effective technique to suppress shadows and a novel block based approach to utilize the local spatial information. The proposed model was tested on numerous complex scenes and results shows a significant performance improvement over standard model.

Keywords

Codebook Video Segmentation Background Subtraction Mixture of Gaussians On line Learning Online Clustering 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Munir Shah
    • 1
  • Jeremiah Deng
    • 1
  • Brendon Woodford
    • 1
  1. 1.Department of Information ScienceUniversity of OtagoDunedinNew Zealand

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