Efficient hierarchical method for background subtraction

  • Authors:

  • Yu-Ting Chen;Chu-Song Chen;Chun-Rong Huang;Yi-Ping Hung

  • Affiliations:

  • Institute of Information Science, Academia Sinica, 128 Academia Road, Section 2, Nankang, Taipei 115, Taiwan and Department of Computer Science and Information Engineering, National Taiwan Univers ...;Institute of Information Science, Academia Sinica, 128 Academia Road, Section 2, Nankang, Taipei 115, Taiwan and Graduate Institute of Networking and Multimedia, National Taiwan University, 1 Roos ...;Institute of Information Science, Academia Sinica, 128 Academia Road, Section 2, Nankang, Taipei 115, Taiwan;Institute of Information Science, Academia Sinica, 128 Academia Road, Section 2, Nankang, Taipei 115, Taiwan and Department of Computer Science and Information Engineering, National Taiwan Univers ...

  • Venue:
  • Pattern Recognition
  • Year:
  • 2007

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Abstract

Detecting moving objects by using an adaptive background model is a critical component for many vision-based applications. Most background models were maintained in pixel-based forms, while some approaches began to study block-based representations which are more robust to non-stationary backgrounds. In this paper, we propose a method that combines pixel-based and block-based approaches into a single framework. We show that efficient hierarchical backgrounds can be built by considering that these two approaches are complementary to each other. In addition, a novel descriptor is proposed for block-based background modeling in the coarse level of the hierarchy. Quantitative evaluations show that the proposed hierarchical method can provide better results than existing single-level approaches.