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A hand tracking algorithm with particle filter and improved GVF snake model

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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.

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Authors and Affiliations

  1. School of Electrical and Information Engineering, Tianjin University, Tianjin, 300072, China

    Yi-qi Sun  (孙一奇), Ai-guo Wu  (吴爱国), Na Dong  (董娜) & Yi-zhe Shao  (邵一哲)

Authors
  1. Yi-qi Sun  (孙一奇)
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  2. Ai-guo Wu  (吴爱国)
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  3. Na Dong  (董娜)
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  4. Yi-zhe Shao  (邵一哲)
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Corresponding author

Correspondence to Ai-guo Wu  (吴爱国).

Additional information

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).

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Sun, Yq., Wu, Ag., Dong, N. et al. A hand tracking algorithm with particle filter and improved GVF snake model. Optoelectron. Lett. 13, 314–317 (2017). https://doi.org/10.1007/s11801-017-7061-2

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  • DOI: https://doi.org/10.1007/s11801-017-7061-2

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