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Motion Based Foreground Detection and Poselet Motion Features for Action Recognition

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Computer Vision -- ACCV 2014 (ACCV 2014)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 9007))

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Abstract

For action recognition, the actor(s) and the tools they use as well as their motion are of central importance. In this paper, we propose separating foreground items of an action from the background on the basis of motion cues. As a consequence, separate descriptors can be defined for the foreground regions, while combined foreground-background descriptors still capture the context of an action. Also a low-dimensional global camera motion descriptor can be computed. Poselet activations in the foreground area indicate the actor and its pose. We propose tracking these poselets to obtain detailed motion features of the actor. Experiments on the Hollywood2 dataset show that foreground-background separation and the poselet motion features lead to consistently favorable results, both relative to the baseline and in comparison to the current state-of-the-art.

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Author information

Authors and Affiliations

  1. Fraunhofer ITWM, Fraunhofer-Platz 1, Kaiserslautern, Germany

    Erwin Kraft

  2. University of Freiburg, Georges-Köhler-Allee 52, Freiburg, Germany

    Thomas Brox

Authors
  1. Erwin Kraft
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  2. Thomas Brox
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Corresponding author

Correspondence to Erwin Kraft .

Editor information

Editors and Affiliations

  1. Technische Universität München, Garching, Germany

    Daniel Cremers

  2. University of Adelaide, Adelaide, South Australia, Australia

    Ian Reid

  3. Keio University, Yokohama, Kanagawa, Japan

    Hideo Saito

  4. University of California at Merced, Merced, California, USA

    Ming-Hsuan Yang

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Kraft, E., Brox, T. (2015). Motion Based Foreground Detection and Poselet Motion Features for Action Recognition. In: Cremers, D., Reid, I., Saito, H., Yang, MH. (eds) Computer Vision -- ACCV 2014. ACCV 2014. Lecture Notes in Computer Science(), vol 9007. Springer, Cham. https://doi.org/10.1007/978-3-319-16814-2_23

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  • DOI: https://doi.org/10.1007/978-3-319-16814-2_23

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-16813-5

  • Online ISBN: 978-3-319-16814-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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