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Multiple Hypothesis Tracking for Automatic Optical Motion Capture

  • Maurice Ringer
  • Joan Lasenby
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2350)

Abstract

We present a technique for performing the tracking stage of optical motion capture which retains, at each time frame, multiple marker association hypotheses and estimates of the subject’s position. Central to this technique are the equations for calculating the likelihood of a sequence of association hypotheses, which we develop using a Bayesian approach. The system is able to perform motion capture using fewer cameras and a lower frame rate than has been used previously, and does not require the assistance of a human operator. We conclude by demonstrating the tracker on real data and provide an example in which our technique is able to correctly determine all marker associations and standard tracking techniques fail.

Keywords

Visual motion correspondence problem tracking optical motion capture 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Maurice Ringer
    • 1
  • Joan Lasenby
    • 1
  1. 1.Engineering DeptCambridge UniversityCambridgeUK

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