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Human action recognition based on discriminant body regions selection

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Abstract

This paper introduces a new method for human action recognition based on human body skeleton. The proposed method is composed of two phases: an off-line phase which selects the most discriminant human body regions and an online phase to classify the request action. In both phases, we applied the cumulative skeletonized images matrix to extract the action features. The experimental study shows that the proposed method, thanks to salient regions selection and the two-level classification strategy, provides good results comparable in terms of recognition accuracy to the most known and recent state-of-the-art methods.

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Authors and Affiliations

  1. MIRACL-ENETCOM, University of Sfax, 3018, Sfax, Tunisia

    Hazar Mliki

  2. MIRACL-FSS, University of Sfax, 3018, Sfax, Tunisia

    Rabàa Zaafouri & Mohamed Hammami

Authors
  1. Hazar Mliki
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  2. Rabàa Zaafouri
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  3. Mohamed Hammami
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Correspondence to Hazar Mliki.

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Mliki, H., Zaafouri, R. & Hammami, M. Human action recognition based on discriminant body regions selection. SIViP 12, 845–852 (2018). https://doi.org/10.1007/s11760-017-1227-z

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  • DOI: https://doi.org/10.1007/s11760-017-1227-z

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