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Continuously Tracking Objects Across Multiple Widely Separated Cameras

  • Yinghao Cai
  • Wei Chen
  • Kaiqi Huang
  • Tieniu Tan
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4843)

Abstract

In this paper, we present a new solution to the problem of multi-camera tracking with non-overlapping fields of view. The identities of moving objects are maintained when they are traveling from one camera to another. Appearance information and spatio-temporal information are explored and combined in a maximum a posteriori (MAP) framework. In computing appearance probability, a two-layered histogram representation is proposed to incorporate spatial information of objects. Diffusion distance is employed to histogram matching to compensate for illumination changes and camera distortions. In deriving spatio-temporal probability, transition time distribution between each pair of entry zone and exit zone is modeled as a mixture of Gaussian distributions. Experimental results demonstrate the effectiveness of the proposed method.

Keywords

Entry Zone Histogram Match Exit Zone Appearance Probability Appearance Information 
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 2007

Authors and Affiliations

  • Yinghao Cai
    • 1
  • Wei Chen
    • 1
  • Kaiqi Huang
    • 1
  • Tieniu Tan
    • 1
  1. 1.National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, P.O.Box 2728, Beijing, 100080China

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