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Online Action Recognition by Template Matching

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Health Information Science (HIS 2013)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 7798))

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Abstract

Human action recognition from video has attracted great attentions from various communities due to its wide applications. Regarded as an effective way to analyze human movements, human skeleton is extracted and represents human body as dots and lines, Recently, depth-cameras make skeleton tracking become practical. Based on the extraction and template matching, we develop a system for online human action segmentation and recognition in this paper. We proposed a method to generate action templates that can be used to represent intra-class variations. We then adopted efficient subsequence matching algorithm for online process. The experimental results demonstrated the effectiveness and efficiency of our system.

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Author information

Authors and Affiliations

  1. NIT, Zhejiang University, 1 Xuefu Road, Ningbo, China

    Xin Zhao & Hao Lan Zhang

  2. School of ITEE, The University of Queensland, Australia

    Xin Zhao, Sen Wang & Xue Li

  3. The Australian E-Health Research Centre, CSIRO, Australia

    Xin Zhao & Sen Wang

Authors
  1. Xin Zhao
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  2. Sen Wang
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  3. Xue Li
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  4. Hao Lan Zhang
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Editor information

Editors and Affiliations

  1. Centre for Applied Informatics, Victoria University, 3011, Melbourne, VIC, Australia

    Guangyan Huang  & Jing He  & 

  2. School of Information System, Computing, and Mathematics, Brunel University, UB8 3PH, London, UK

    Xiaohui Liu

  3. Department of Computer Science, Ostfalia University of Applied Sciences, Salzdahlumer Str. 46/48, Wolfenbüttel, Germany

    Frank Klawonn

  4. Health Economics, Primary Care and Population Sciences, Faculty of Medicine, University of Southampton, Southampton, UK

    Guiqing Yao

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© 2013 Springer-Verlag Berlin Heidelberg

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Zhao, X., Wang, S., Li, X., Zhang, H.L. (2013). Online Action Recognition by Template Matching. In: Huang, G., Liu, X., He, J., Klawonn, F., Yao, G. (eds) Health Information Science. HIS 2013. Lecture Notes in Computer Science, vol 7798. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37899-7_25

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  • DOI: https://doi.org/10.1007/978-3-642-37899-7_25

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-37898-0

  • Online ISBN: 978-3-642-37899-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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