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Vision-Based Human Action Recognition in Surveillance Videos Using Motion Projection Profile Features

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Mining Intelligence and Knowledge Exploration (MIKE 2015)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9468))

Abstract

Human Action Recognition (HAR) is a dynamic research area in pattern recognition and artificial Intelligence. The area of human action recognition consistently focuses on changes in the scene of a subject with reference to time, since motion information can prudently depict the action. This paper depicts a novel framework for action recognition based on Motion Projection Profile (MPP) features of the difference image, representing various levels of a person’s posture. The motion projection profile features consist of the measure of moving pixel of each row, column and diagonal (left and right) of the difference image and gives adequate motion information to recognize the instantaneous posture of the person. The experiments are carried out using WEIZMANN and AUCSE datasets and the extracted features are modeled by the GMM classifier for recognizing human actions. In the experimental results, GMM exhibit effectiveness of the proposed method with an overall accuracy rate of 94.30 % for WEIZMANN dataset and 92.49 % for AUCSE dataset.

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Authors and Affiliations

  1. Speech and Vision Lab, Department of Computer Science and Engineering, Annamalai University, Annamalainagar, Tamilnadu, India

    J. Arunnehru & M. Kalaiselvi Geetha

Authors
  1. J. Arunnehru
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  2. M. Kalaiselvi Geetha
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Corresponding author

Correspondence to J. Arunnehru .

Editor information

Editors and Affiliations

  1. Norwegian Univ. of Science & Technology, Trondheim, Norway

    Rajendra Prasath

  2. Intl Inst of Info Tech Hyderabad, Hyderabad, India

    Anil Kumar Vuppala

  3. V.H.N.S.N.College (Autonomous), Virudhunagar, Tamil Nadu, India

    T. Kathirvalavakumar

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© 2015 Springer International Publishing Switzerland

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Arunnehru, J., Geetha, M.K. (2015). Vision-Based Human Action Recognition in Surveillance Videos Using Motion Projection Profile Features. In: Prasath, R., Vuppala, A., Kathirvalavakumar, T. (eds) Mining Intelligence and Knowledge Exploration. MIKE 2015. Lecture Notes in Computer Science(), vol 9468. Springer, Cham. https://doi.org/10.1007/978-3-319-26832-3_43

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  • DOI: https://doi.org/10.1007/978-3-319-26832-3_43

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-26831-6

  • Online ISBN: 978-3-319-26832-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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