A local-motion-based probabilistic model for visual tracking

  • Authors:

  • M. Kristan;J. Perš;S. Kovačič;A. Leonardis

  • Affiliations:

  • Faculty of Computer and Information Science, University of Ljubljana, Slovenia and Faculty of Electrical Engineering, University of Ljubljana, Slovenia;Faculty of Electrical Engineering, University of Ljubljana, Slovenia;Faculty of Electrical Engineering, University of Ljubljana, Slovenia;Faculty of Computer and Information Science, University of Ljubljana, Slovenia

  • Venue:
  • Pattern Recognition
  • Year:
  • 2009

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Abstract

Color-based tracking is prone to failure in situations where visually similar targets are moving in a close proximity or occlude each other. To deal with the ambiguities in the visual information, we propose an additional color-independent visual model based on the target's local motion. This model is calculated from the optical flow induced by the target in consecutive images. By modifying a color-based particle filter to account for the target's local motion, the combined color/local-motion-based tracker is constructed. We compare the combined tracker to a purely color-based tracker on a challenging dataset from hand tracking, surveillance and sports. The experiments show that the proposed local-motion model largely resolves situations when the target is occluded by, or moves in front of, a visually similar object.