Dynamic Context for Tracking behind Occlusions

  • Fei Xiong
  • Octavia I. Camps
  • Mario Sznaier
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7576)


Tracking objects in the presence of clutter and occlusion remains a challenging problem. Current approaches often rely on a priori target dynamics and/or use nearly rigid image context to determine the target position. In this paper, a novel algorithm is proposed to estimate the location of a target while it is hidden due to occlusion. The main idea behind the algorithm is to use contextual dynamical cues from multiple supporter features which may move with the target, move independently of the target, or remain stationary. These dynamical cues are learned directly from the data without making prior assumptions about the motions of the target and/or the support features. As illustrated through several experiments, the proposed algorithm outperforms state of the art approaches under long occlusions and severe camera motion.


dynamics-based tracking occlusion context 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Fei Xiong
    • 1
  • Octavia I. Camps
    • 1
  • Mario Sznaier
    • 1
  1. 1.Dept. of Electrical and Computer EngineeringNortheastern UniversityBostonUSA

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