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Discovering Structures in Video Databases

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Foundations of Intelligent Systems (ISMIS 2003)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2871))

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Abstract

This paper presents an automated technique that combines manual annotations and knowledge produced by an automatic content characterization technique to build higher level abstraction of video content. We develop a method based on concept languages for automatically discovering structural associations within video sequences. The obtained abstraction of the contents of video sequences can be used, by navigating the tree structure.

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References

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Author information

Authors and Affiliations

  1. LIRIS Université Claude Bernard Lyon 1, 43, boulevard du 11 novembre 1918, 69622, Villeurbanne, France

    Hicham Hajji & Mohand-Said Hacid

  2. Laboratoire LIMOS, ISIMA – Campus des Cezeaux, B.P. 125, 63173, AUBIERE Cedex, France

    Farouk Toumani

Authors
  1. Hicham Hajji
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  2. Mohand-Said Hacid
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  3. Farouk Toumani
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Editor information

Editors and Affiliations

  1. The International WIC Institute, Beijing University of Technology, China

    Ning Zhong

  2. Department of Computer Science, University of North Carolina, NC 28223, Charlotte, USA

    Zbigniew W. Raś

  3. Shimane University, 89-1 Enya-cho Izumo, 6938501, Shimane, Japan

    Shusaku Tsumoto

  4. Department of Informatics, Graduate School of Information Science and Electrical Engineering, Kyushu University, 744 Motooka, Nishi, 819-0395, Fukuoka, Japan

    Einoshin Suzuki

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© 2003 Springer-Verlag Berlin Heidelberg

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Hajji, H., Hacid, MS., Toumani, F. (2003). Discovering Structures in Video Databases. In: Zhong, N., Raś, Z.W., Tsumoto, S., Suzuki, E. (eds) Foundations of Intelligent Systems. ISMIS 2003. Lecture Notes in Computer Science(), vol 2871. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-39592-8_84

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  • DOI: https://doi.org/10.1007/978-3-540-39592-8_84

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-20256-1

  • Online ISBN: 978-3-540-39592-8

  • eBook Packages: Springer Book Archive

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