Robust Non-rigid Object Tracking Using Point Distribution Manifolds

  • Tom Mathes
  • Justus H. Piater
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4174)


We present an approach to non-rigid object tracking designed to handle textured objects in crowded scenes captured by non-static cameras. For this purpose, groups of low-level features are combined into a model describing both the shape and the appearance of the object. This results in remarkable robustness to severe partial occlusions, since overlapping objects are unlikely to be indistinguishable in appearance, configuration and velocity all at the same time. The model is learnt incrementally and adapts to varying illumination conditions and target shape and appearance, and is thus applicable to any kind of object. Results on real-world sequences demonstrate the performance of the proposed tracker. The algorithm is implemented with the aim of achieving near real-time performance.


Feature Point Soccer Player Interest Point Object Tracking Video Surveillance 
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

  • Tom Mathes
    • 1
  • Justus H. Piater
    • 1
  1. 1.Department of Electrical Engineering and Computer Science , Montefiore InstituteUniversity of LiègeLiègeBelgium

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