Multiple Object Tracking Via Multi-layer Multi-modal Framework

  • Hang-Bong Kang
  • Kihong Chun
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4522)


In this paper, we propose a new multiple object tracking method via multi-layer multi-modal framework. To handle erroneous merge and labeling problem in multiple object tracking, we use a multi layer representation of dynamic Bayesian network and modified sampling method. For robust visual tracking, our dynamic Bayesian network based tracker fuses multi-modal features such as color and edge orientation histogram. The proposed method was evaluated under several real situations and promising results were obtained.


Target Object Dynamic Bayesian Network Edge Orientation Multiple Object Tracking Label Problem 
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 Berlin Heidelberg 2007

Authors and Affiliations

  • Hang-Bong Kang
    • 1
  • Kihong Chun
    • 1
  1. 1.Dept. of Computer Eng., Catholic University of Korea, #43-1 Yokkok 2-dong Wonmi-Gu, Puchon, Kyonggi-DoKorea

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