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Human Action Recognition Using LBP-TOP as Sparse Spatio-Temporal Feature Descriptor

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Computer Analysis of Images and Patterns (CAIP 2009)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 5702))

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Abstract

In this paper we apply the Local Binary Pattern on Three Orthogonal Planes (LBP-TOP) descriptor to the field of human action recognition. A video sequence is described as a collection of spatial-temporal words after the detection of space-time interest points and the description of the area around them. Our contribution has been in the description part, showing LBP-TOP to be a promising descriptor for human action classification purposes. We have also developed several extensions to the descriptor to enhance its performance in human action recognition, showing the method to be computationally efficient.

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Author information

Authors and Affiliations

  1. Philips Research, Eindhoven, The Netherlands

    Riccardo Mattivi & Ling Shao

Authors
  1. Riccardo Mattivi
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  2. Ling Shao
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Editor information

Editors and Affiliations

  1. Department of Mathematics and Computer Science, University of Münster, Einsteinstrasse 62, 48149, Münster, Germany

    Xiaoyi Jiang

  2. Institute of Mathematics and Computing Science, University of Groningen, Nijenborgh 9, 9747, Groningen, AG, The Netherlands

    Nicolai Petkov

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© 2009 Springer-Verlag Berlin Heidelberg

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Mattivi, R., Shao, L. (2009). Human Action Recognition Using LBP-TOP as Sparse Spatio-Temporal Feature Descriptor. In: Jiang, X., Petkov, N. (eds) Computer Analysis of Images and Patterns. CAIP 2009. Lecture Notes in Computer Science, vol 5702. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03767-2_90

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  • DOI: https://doi.org/10.1007/978-3-642-03767-2_90

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-03766-5

  • Online ISBN: 978-3-642-03767-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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