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Human Action Recognition Using 2DPCA-DMM Representation and GA-SVM in Depth Sequences

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Knowledge and Systems Engineering

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 326))

Abstract

Automatic human action recognition is an interesting and challenging problem in computer vision. Furthermore, it has wide range of real-world applications such as human-machine interaction, surveillance system, data-driven automation, smart home and robotics. In the recent years, the availability of 3D sensors has recently made it possible to capture depth maps in real time, which simplifies variety of visual recognition tasks, including action classification, 3D reconstruction, etc? We address here the problem of human action recognition in depth sequences. On one hand, we present a novel for human action recognition based on 2DPCA applied to DMM. Then, we project feature matrixes into difference spaces to create robust action representation. Finally, we use GA to create the coefficients for multi- SVM classifiers. Our approach is systematically examined on benchmark datasets such as MSR-Gesture3D and MSR-Action3D which results with an overall accuracy of 91.32% on the MSR-Action3D and 94.89% on the MSR-Gesture3D. The experimental results also indicated that the extraction of features and representation are effective and shows the effective of our proposal.

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Authors and Affiliations

  1. Computer Vision and Robotics Department, University of Science - VNU - HCMC, Ho Chi Minh, Vietnam

    Vo Hoai Viet, Ly Quoc Ngoc & Tran Thai Son

Authors
  1. Vo Hoai Viet
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  2. Ly Quoc Ngoc
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  3. Tran Thai Son
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Corresponding author

Correspondence to Vo Hoai Viet .

Editor information

Editors and Affiliations

  1. Faculty of Information Technology, VNU University of Engineering and Technology, Hanoi, Vietnam

    Viet-Ha Nguyen

  2. Faculty of Information Technology, VNU University of Engineering and Technology, Hanoi, Vietnam

    Anh-Cuong Le

  3. School of Knowledge Science, Japan Advanced Institute of Science and Technology, Nomi, Ishikawa, Japan

    Van-Nam Huynh

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Viet, V.H., Ngoc, L.Q., Son, T.T. (2015). Human Action Recognition Using 2DPCA-DMM Representation and GA-SVM in Depth Sequences. In: Nguyen, VH., Le, AC., Huynh, VN. (eds) Knowledge and Systems Engineering. Advances in Intelligent Systems and Computing, vol 326. Springer, Cham. https://doi.org/10.1007/978-3-319-11680-8_36

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  • DOI: https://doi.org/10.1007/978-3-319-11680-8_36

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-11679-2

  • Online ISBN: 978-3-319-11680-8

  • eBook Packages: EngineeringEngineering (R0)

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