A hand tracking algorithm with particle filter and improved GVF snake model
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School of Electrical and Information Engineering, Tianjin University, Tianjin 300072, China

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    Abstract:

    To solve the problem that the accurate information of hand cannot be obtained by particle filter, a hand tracking algorithm based on particle filter combined with skin-color adaptive gradient vector flow (GVF) snake model is proposed. Adaptive GVF and skin color adaptive external guidance force are introduced to the traditional GVF snake model, guiding the curve to quickly converge to the deep concave region of hand contour and obtaining the complex hand contour accurately. This algorithm realizes a real-time correction of the particle filter parameters, avoiding the particle drift phenomenon. Experimental results show that the proposed algorithm can reduce the root mean square error of the hand tracking by 53%, and improve the accuracy of hand tracking in the case of complex and moving background, even with a large range of occlusion. This work has been supported by the National Natural Sciencal Foundation of China (No.61403274), and the Tianjin Technology Project of Intelligent Manufacturing (No.15ZXZNGX00160). E-mail:agwu@tju.edu.cn

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SUN Yi-qi, WU Ai-guo, DONG Na, and SHAO Yi-zhe. A hand tracking algorithm with particle filter and improved GVF snake model[J]. Optoelectronics Letters,2017,13(4):314-317

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History
  • Received:March 17,2017
  • Revised:April 14,2017
  • Adopted:
  • Online: September 29,2017
  • Published: