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SVM-Based Approach for Human Daily Motion Recognition

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International Conference on Biomedical and Health Informatics (ICBHI 2015)

Part of the book series: IFMBE Proceedings ((IFMBE,volume 64))

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Abstract

The application of human motion analysis and recognition is very extensive, involving national defense, medical, film production and many other areas.

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References

  1. R. Green, L. Guan. Quantifying and recognizing human movement patterns from monocular video images-Part I: A new framework for modeling human motion. IEEE Transactions on Circuits and systems for Video Technology, Special Issue on Image and Video-Based Biometrics, 14: pp. 179–190, 2004.

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  2. I. Laptev, B. Caputo, Recognizing Human Actions: A Local SVM Approach, Pattern Recognition, 2004.

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Acknowledgements

Research supported by the High-End Talent Oversea Returnees Foundation of Shenzhen (KQC201109020052A), Basic Research Foundation (Outstanding Young Investigator Track) of Shenzhen (JC201005260124A), and the National Science Foundation of China (81000647).

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Authors and Affiliations

  1. Department of Electronic & Information Engineering, Harbin Institute of Technology Shenzhen Graduate School, Shenzhen, China

    Haitao Yang, Xinrong Zhang, Mengting Chen & Heather T. Ma

Authors
  1. Haitao Yang
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  2. Xinrong Zhang
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  3. Mengting Chen
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  4. Heather T. Ma
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Corresponding author

Correspondence to Heather T. Ma .

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Editors and Affiliations

  1. The Chinese University of Hong Kong, Hong Kong, China

    Yuan-Ting Zhang

  2. Universidade De Coimbra, Coimbra, Portugal

    Paulo Carvalho

  3. Faculty of Electrical Engineering and Computing, University of Zagreb, Zagreb, Croatia

    Ratko Magjarevic

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© 2019 Springer Nature Singapore Pte Ltd.

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Yang, H., Zhang, X., Chen, M., Ma, H.T. (2019). SVM-Based Approach for Human Daily Motion Recognition. In: Zhang, YT., Carvalho, P., Magjarevic, R. (eds) International Conference on Biomedical and Health Informatics. ICBHI 2015. IFMBE Proceedings, vol 64. Springer, Singapore. https://doi.org/10.1007/978-981-10-4505-9_32

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  • DOI: https://doi.org/10.1007/978-981-10-4505-9_32

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-4504-2

  • Online ISBN: 978-981-10-4505-9

  • eBook Packages: EngineeringEngineering (R0)

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