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Dexterous Hand Motion Classification and Recognition Based on Multimodal Sensing

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Intelligent Robotics and Applications (ICIRA 2017)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10462))

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Abstract

Human hand motions analysis is an essential research topic in recent applications, especially for dexterous robot hand manipulation learning from human hand skills. It provides important information about gestures, moving, speed and the control force captured via multimodal sensing technologies. This paper presents a comprehensive discussion of the nature of human hand motions in terms of simple motions, such as grasps and gestures, and complex motions, e.g. in-hand manipulations and re-grasps. And then, a novel multimodal sensing based hand motion capture system is proposed to acquire the sensory information. By using an adaptive directed acyclic graph algorithm, the experimental results show the proposed system has a higher recognition rate compared with those with individual sensing technologies.

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Acknowledgment

This work is partially supported by Natural Science Foundation of China (Grant No. 51575412), the Fundamental Research Funds for the Central Universities (Grant No. 2016-JL-011). Also, the authors would like to acknowledge the reviewers for their valuable comments and suggestions that helped to improve the quality of the manuscript.

Author information

Authors and Affiliations

  1. School of Automation, Wuhan University of Technology, Wuhan, China

    Yaxu Xue & Kui Xiang

  2. School of Computing, The University of Portsmouth, Portsmouth, UK

    Yaxu Xue, Zhaojie Ju & Honghai Liu

  3. School of Electrical and Mechanical Engineering, Pingdingshan University, Pingdingshan, China

    Yaxu Xue

  4. College of Engineering, Swansea University, Swansea, UK

    Chenguang Yang

Authors
  1. Yaxu Xue
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  2. Zhaojie Ju
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  3. Kui Xiang
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  4. Chenguang Yang
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  5. Honghai Liu
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Corresponding author

Correspondence to Zhaojie Ju .

Editor information

Editors and Affiliations

  1. School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, China

    YongAn Huang

  2. School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, China

    Hao Wu

  3. Institute of Industrial Research, University of Portsmouth, Portsmouth, United Kingdom

    Honghai Liu

  4. School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, China

    Zhouping Yin

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Xue, Y., Ju, Z., Xiang, K., Yang, C., Liu, H. (2017). Dexterous Hand Motion Classification and Recognition Based on Multimodal Sensing. In: Huang, Y., Wu, H., Liu, H., Yin, Z. (eds) Intelligent Robotics and Applications. ICIRA 2017. Lecture Notes in Computer Science(), vol 10462. Springer, Cham. https://doi.org/10.1007/978-3-319-65289-4_43

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  • DOI: https://doi.org/10.1007/978-3-319-65289-4_43

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-65288-7

  • Online ISBN: 978-3-319-65289-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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