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Occlusion Detection and Tracking Method Based on Bayesian Decision Theory

  • Yan Zhou
  • Bo Hu
  • Jianqiu Zhang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4319)

Abstract

In order to track an occluded target in an image sequence, the Bayesian decision theory is, here, introduced to the problem of distinguishing occlusions and appearance changes according to their different risk possibilities. A new target template combining image intensity and histogram is designed. The corresponding updating method is also derived based on particle filter. If the target is totally occluded by another target, the template can be kept unchanged. The occlusion of a target will not influence tracking. Simulation results show that the presented method can efficiently justify whether the occlusion occurs and realize target tracking in image sequences even though the tracked target is totally occluded with long time.

Keywords

Particle Filter Target Tracking Appearance Change Tracking Procedure Importance Function 
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 2006

Authors and Affiliations

  • Yan Zhou
    • 1
  • Bo Hu
    • 1
  • Jianqiu Zhang
    • 1
  1. 1.Department of Electronic EngineeringFudan UniversityShanghai

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