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View-independent action recognition: a hybrid approach

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Abstract

In this paper, we propose a new framework for view independent action recognition, which uses a combination of a view-dependent representation and a view-independent representation. The view-dependent representation reduces the number of possible action’s labels prior to the view-independent representation. We used the entropy of silhouette’s distance transformation as view-dependent representation and the self-similarity matrix of the trajectory of uniformly distributed feature points over the human body as view-independent representation. The experiment results show that the proposed method outperforms recent action recognition approaches despite its low computational cost.

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Authors and Affiliations

  1. Department of Computer Engineering and Information Technology, Amirkabir University of Technology, Tehran, Iran

    Seyed Mohammad Hashemi & Mohammad Rahmati

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  1. Seyed Mohammad Hashemi
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  2. Mohammad Rahmati
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Correspondence to Mohammad Rahmati.

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Hashemi, S.M., Rahmati, M. View-independent action recognition: a hybrid approach. Multimed Tools Appl 75, 6755–6775 (2016). https://doi.org/10.1007/s11042-015-2606-5

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