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Automatic Video Activity Recognition

  • Chapter
Multimedia Analysis, Processing and Communications

Part of the book series: Studies in Computational Intelligence ((SCI,volume 346))

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Abstract

With the demands on public security and the availability of large storage systems, an increasing number of video surveillance systems are being deployed all over the world to help people detect interesting target events. However, most of these systems require intensive human monitoring, or require human operators to review video footage corresponding to extended periods of time, only to find a few short clips that are of interest. The problem fosters a demand of an automatic computer surveillance system, which can assist the human operators in identifying possible interesting events. This challenge has attracted researchers from different domains, leading to a variety of proposed approaches, particularly in the field of human activity recognition. These approaches vary in the choice of representation and methodologies as well. This chapter gives a survey and reviews the state of the art approaches to automatic human activity recognition in videos.

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Author information

Authors and Affiliations

  1. University of Washington, Seattle, WA, 98195

    Haowei Liu & Ming-Ting Sun

  2. IBM T.J Watson Research Center, Hawthorn, NY, 10532

    Rogerio Feris

Authors
  1. Haowei Liu
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  2. Ming-Ting Sun
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  3. Rogerio Feris
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Editor information

Editors and Affiliations

  1. School of Computer Engineering , Nanyang Technological University, 639798, Singapore

    Weisi Lin  & Dacheng Tao  & 

  2. Intelligent Systems Laboratory Systems Research Institute , Polish Academy of Sciences, Poland

    Janusz Kacprzyk

  3. Department of Computing , Hong Kong Polytechnic University, Hung Hom, Hong Kong

    Zhu Li

  4. School of Electronic Engineering and Computer Science, Queen Mary, University of London, London, U.K.

    Ebroul Izquierdo

  5. TCL-Thomson Electronics , Santa Clara, California

    Haohong Wang

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© 2011 Springer-Verlag Berlin Heidelberg

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Liu, H., Sun, MT., Feris, R. (2011). Automatic Video Activity Recognition. In: Lin, W., Tao, D., Kacprzyk, J., Li, Z., Izquierdo, E., Wang, H. (eds) Multimedia Analysis, Processing and Communications. Studies in Computational Intelligence, vol 346. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19551-8_11

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  • DOI: https://doi.org/10.1007/978-3-642-19551-8_11

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-19550-1

  • Online ISBN: 978-3-642-19551-8

  • eBook Packages: EngineeringEngineering (R0)

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