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Vision Based Semantic Analysis of Surveillance Videos

  • Chapter
Semantic Hyper/Multimedia Adaptation

Part of the book series: Studies in Computational Intelligence ((SCI,volume 418))

Abstract

As recent research in automatic surveillance systems has attracted many cross-domain researchers, a large-number of algorithms have been proposed for automating surveillance systems. The objective of this chapter is twofold: First, we present an extensive survey of different techniques that have been proposed for surveillance systems categorised into motion analysis, visual feature extraction and indexing. Second, an integrated surveillance framework for unsupervised object indexing is developed to study and evaluate the performance of visual features. The study focuses on two characteristics highly related with human visual perception, colour and texture. The set of visual features under analysis comprises two categories, new leading visual features versus state-of-the-art MPEG-7 visual features. The evaluation of the framework is carried out with AVSS 2007 and CamVid 2008 datasets.

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Authors and Affiliations

  1. Multimedia and Vision Research Group, School of Electronic Engineering and Computer Science, Queen Mary, University of London, Mile End Road, London, E1 4NS, UK

    Virginia Fernandez Arguedas, Qianni Zhang, Krishna Chandramouli & Ebroul Izquierdo

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  1. Virginia Fernandez Arguedas
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  2. Qianni Zhang
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  3. Krishna Chandramouli
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  4. Ebroul Izquierdo
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Correspondence to Virginia Fernandez Arguedas .

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Editors and Affiliations

  1. , Department of Computer Science, University of Central Greece, Lamia, 35100, Greece

    Ioannis E. Anagnostopoulos

  2. in Bratislava, Institute of Informatics, Slovak University of Technology, Ilkovičova 3, Bratislava, 842 16, Slovakia

    Mária Bieliková

  3. Department of Informatics, Ionian University, Tsirigoti Square 7, Corfu, 49100, Greece

    Phivos Mylonas

  4. , Dept. of Communication and Internet Stud, Cyprus University of Technology, 31 Archbishop Kyprianos Str., Lemesos, 3036, Cyprus

    Nicolas Tsapatsoulis

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Arguedas, V.F., Zhang, Q., Chandramouli, K., Izquierdo, E. (2013). Vision Based Semantic Analysis of Surveillance Videos. In: Anagnostopoulos, I., Bieliková, M., Mylonas, P., Tsapatsoulis, N. (eds) Semantic Hyper/Multimedia Adaptation. Studies in Computational Intelligence, vol 418. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28977-4_3

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  • DOI: https://doi.org/10.1007/978-3-642-28977-4_3

  • Publisher Name: Springer, Berlin, Heidelberg

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