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Semantic Content Analysis of Video: Issues and Trends

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Multimedia Analysis, Processing and Communications

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

Abstract

Key issues in bridging the semantic gap for content analysis of video include flexibility required from the software, real time implementation and cost effectiveness. In recent years industry has begun to take a more realistic view of what to expect from video content analysis systems in the near future. This chapter presents the state-of–the-art trends in semantic video analysis in industry. The key challenges in bridging the semantic gap are discussed. It also presents the research trends in video analytics.

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Author information

Authors and Affiliations

  1. School of Computer Science, University of Manchester, U.K.

    Aparna Garg & Allan Ramsay

Authors
  1. Aparna Garg
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  2. Allan Ramsay
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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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Garg, A., Ramsay, A. (2011). Semantic Content Analysis of Video: Issues and Trends. 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_16

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  • DOI: https://doi.org/10.1007/978-3-642-19551-8_16

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-19550-1

  • Online ISBN: 978-3-642-19551-8

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