Hand Tracking Using a Quadric Surface Model and Bayesian Filtering

  • Roberto Cipolla
  • Bjorn Stenger
  • Arasanathan Thayananthan
  • Philip H. S. Torr
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2768)


Within this paper a technique for model-based 3D hand tracking is presented. A hand model is built from a set of truncated quadrics, approximating the anatomy of a real hand with few parameters. Given that the projection of a quadric onto the image plane is a conic, the contours can be generated efficiently. These model contours are used as shape templates to evaluate possible matches in the current frame. The evaluation is done within a hierarchical Bayesian filtering framework, where the posterior distribution is computed efficiently using a tree of templates. We demonstrate the effectiveness of the technique by using it for tracking 3D articulated and non-rigid hand motion from monocular video sequences in front of a cluttered background.


Joint Angle Hand Motion Leaf Level Cluttered Background Camera Centre 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Roberto Cipolla
    • 1
  • Bjorn Stenger
    • 1
  • Arasanathan Thayananthan
    • 1
  • Philip H. S. Torr
    • 2
  1. 1.Department of EngineeringUniversity of CambridgeCambridgeUK
  2. 2.Microsoft Research Ltd.CambridgeUK

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