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A novel approach for recognition of human actions with semi-global features

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Abstract

In this study a new approach is presented for the recognition of human actions of everyday life with a fixed camera. The originality of the presented method consists in characterizing sequences by a temporal succession of semi-global features, which are extracted from “space-time micro-volumes”. The advantage of this approach lies in the use of robust features (estimated on several frames) associated with the ability to manage actions with variable durations and easily segment the sequences with algorithms that are specific to time-varying data. Each action is actually characterized by a temporal sequence that constitutes the input of a Hidden Markov Model system for the recognition. Results presented of 1,614 sequences performed by several persons validate the proposed approach.

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Authors and Affiliations

  1. Institut Systèmes Intelligents et Robotique (ISIR), Université Pierre et Marie Curie, 4 place Jussieu, Case courrier 252, 75252, Paris cedex 05, France

    Catherine Achard, Xingtai Qu, Arash Mokhber & Maurice Milgram

Authors
  1. Catherine Achard
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  2. Xingtai Qu
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  3. Arash Mokhber
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  4. Maurice Milgram
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Correspondence to Catherine Achard.

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Achard, C., Qu, X., Mokhber, A. et al. A novel approach for recognition of human actions with semi-global features. Machine Vision and Applications 19, 27–34 (2008). https://doi.org/10.1007/s00138-007-0074-2

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  • DOI: https://doi.org/10.1007/s00138-007-0074-2

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