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Motion-Based Feature Extraction and Ascendant Hierarchical Classification for Video Indexing and Retrieval

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Visual Information and Information Systems (VISUAL 1999)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1614))

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Abstract

This paper describes an original approach for motion characterization witha view to content-based video indexing and retrieval. A statistical analysis of temporal cooccurrence distributions of relevant local motion-based measures is exploited to compute global motion descriptors, which allows to handle diverse motion situations. These features are used in an ascendant hierarchical classification procedure to supply a meaningful hierarchy from a set of sequences. Results of classification and retrieval on a database of video sequences are reported.

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Author information

Authors and Affiliations

  1. IRISA / CNRS, Campus universitaire de Beaulieu, 35042, Rennes Cedex, France

    Ronan Fable

  2. IRISA / INRIA, Campus universitaire de Beaulieu, 35042, Rennes Cedex, France

    Patrick Bouthemy

Authors
  1. Ronan Fable
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  2. Patrick Bouthemy
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Editor information

Editors and Affiliations

  1. Computer Science Department, Leiden University, Niels Bohrweg 1, 2333 CA, Leiden, The Netherlands

    Dionysius P. Huijsmans

  2. Research Institute Computer Science, University of Amsterdam, Kruislaan 403, 1098 SJ, Amsterdam, The Netherlands

    Arnold W. M. Smeulders

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© 1999 Springer-Verlag Berlin Heidelberg

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Fable, R., Bouthemy, P. (1999). Motion-Based Feature Extraction and Ascendant Hierarchical Classification for Video Indexing and Retrieval. In: Huijsmans, D.P., Smeulders, A.W.M. (eds) Visual Information and Information Systems. VISUAL 1999. Lecture Notes in Computer Science, vol 1614. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48762-X_28

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  • DOI: https://doi.org/10.1007/3-540-48762-X_28

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-66079-8

  • Online ISBN: 978-3-540-48762-3

  • eBook Packages: Springer Book Archive

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