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Recognition of human actions using texture descriptors

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Abstract

Human motion can be seen as a type of texture pattern. In this paper, we adopt the ideas of spatiotemporal analysis and the use of local features for motion description. Two methods are proposed. The first one uses temporal templates to capture movement dynamics and then uses texture features to characterize the observed movements. We then extend this idea into a spatiotemporal space and describe human movements with dynamic texture features. Following recent trends in computer vision, the method is designed to work with image data rather than silhouettes. The proposed methods are computationally simple and suitable for various applications. We verify the performance of our methods on the popular Weizmann and KTH datasets, achieving high accuracy.

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Authors and Affiliations

  1. Machine Vision Group, University of Oulu, P.O. Box 4500, Oulu, Finland

    Vili Kellokumpu, Guoying Zhao & Matti Pietikäinen

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  1. Vili Kellokumpu
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  2. Guoying Zhao
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  3. Matti Pietikäinen
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Correspondence to Vili Kellokumpu.

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Kellokumpu, V., Zhao, G. & Pietikäinen, M. Recognition of human actions using texture descriptors. Machine Vision and Applications 22, 767–780 (2011). https://doi.org/10.1007/s00138-009-0233-8

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  • DOI: https://doi.org/10.1007/s00138-009-0233-8

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