Joint Probabilistic Techniques for Tracking Multi-Part Objects

  title={Joint Probabilistic Techniques for Tracking Multi-Part Objects},
  author={Christopher Rasmussen and Gregory D. Hager},
Common objects such as people and cars comprise many visual parts and attributes, yet image-based tracking algorithms are often keyed to only one of a target's identifying characteristics. In this paper, we present a framework for combining and sharing information among several state estimation processes operating on the same underlying visual object. Well-known techniques for joint probabilistic data association are adapted to yield increased robustness when multiple trackers attuned to… CONTINUE READING
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