Visual hand tracking using nonparametric sequential belief propagation

Authors:
Wei Liang;Yunde Jia;Cheng Ge
Affiliations:
Department of Computer Science and Engineering, Beijing Institute of Technology, Beijing, P.R. China;Department of Computer Science and Engineering, Beijing Institute of Technology, Beijing, P.R. China;Department of Computer Science and Engineering, Beijing Institute of Technology, Beijing, P.R. China
Venue:
ICIC'05 Proceedings of the 2005 international conference on Advances in Intelligent Computing - Volume Part I
Year:
2005

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Abstract

Hand tracking is a challenging problem due to the complexity of searching in a 20+ degrees of freedom space for an optimal estimate. This paper develops a statistical method for robust visual hand tracking, in which graphical model decoupling different hand joints is performed to represent the hand constraints. Each node of the graphical model represents the position and the orientation of each hand joint in world coordinate. Then, the problem of hand tracking is transformed into an inference of graphical model. We extend Nonparametric Belief Propagation to a sequential process to track hand motion. The Experiment results show that this approach is robust for 3D hand motion tracking.