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A Hand Model Updating Algorithm Based on Mean Shift

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Information Computing and Applications (ICICA 2013)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 391))

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Abstract

To solve the problem of target model changing and influenced tracking results in gesture target tracking process, this paper proposed a gesture model updating and results forecasting algorithm based on Mean Shift. The algorithm firstly uses the background subtraction and skin color detection methods to detect and obtain gesture modeling, and then uses the Mean Shift algorithm to track gesture and update the gesture model, finally uses the Kalman algorithm to predict the gesture tracking results. The experimental results show that this algorithm reduces influence of surrounding environment in gesture tracking process, tracking effect is good.

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Author information

Authors and Affiliations

  1. School of Computer and Communication, Lanzhou University of Technology, 730050, Lanzhou, China

    Xiao Zou, Heng Wang, HongXiang Duan & QiuYu Zhang

Authors
  1. Xiao Zou
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  2. Heng Wang
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  3. HongXiang Duan
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  4. QiuYu Zhang
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Editor information

Editors and Affiliations

  1. Shanghai Jiao Tong University, 800 Dongchuan Road, Dianxinqunlou 1-401, 200240, Shanghai, China

    Yuhang Yang

  2. School of Electrical and Electronic Engineering, Nanyang Technological University, Nanyang Avenue, 639798, Singapore, Singapore

    Maode Ma

  3. College of Science, Hebei United University, 063009, Tangshan, Hebei, China

    Baoxiang Liu

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© 2013 Springer-Verlag Berlin Heidelberg

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Zou, X., Wang, H., Duan, H., Zhang, Q. (2013). A Hand Model Updating Algorithm Based on Mean Shift. In: Yang, Y., Ma, M., Liu, B. (eds) Information Computing and Applications. ICICA 2013. Communications in Computer and Information Science, vol 391. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-53932-9_63

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  • DOI: https://doi.org/10.1007/978-3-642-53932-9_63

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-53931-2

  • Online ISBN: 978-3-642-53932-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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