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Online Bayesian Video Summarization and Linking

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Book cover Image and Video Retrieval (CIVR 2002)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2383))

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Abstract

In this paper, an online Bayesian formulation is presented to detect and describe the most significant key-frames and shot boundaries of a video sequence. Visual information is encoded in terms of a reduced number of degrees of freedom in order to provide robustness to noise, gradual transitions, flashes, camera motion and illumination changes. We present an online algorithm where images are classified according to their appearance contents-pixel values plus shape information- in order to obtain a structured representation from sequential information. This structured representation is presented on a grid where nodes correspond to the location of the representative image for each cluster. Since the estimation process takes simultaneously into account clustering and nodes’ locations in the representation space, key-frames are placed considering visual similarities among neighbors. This fact not only provides a powerful tool for video navigation but also offers an organization for posterior higher-level analysis such as identifying pieces of news, interviews, etc.

This work was supported by CICYT grant TEL99-1206-C02-02 and CERTAP Generalitat de Catalunya.

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Author information

Authors and Affiliations

  1. Centre de Visió per Computador (CVC), Dept. Informàtica, Universitat Autònoma de Barcelona, Barcelona, Spain, 08193, Bellaterra

    Xavier Orriols & Xavier Binefa

Authors
  1. Xavier Orriols
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  2. Xavier Binefa
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Editor information

Editors and Affiliations

  1. LIACS Media Lab, Leiden University, Niels Bohrweg 1, 2333 CA, Leiden, The Netherlands

    Michael S. Lew  & Nicu Sebe  & 

  2. Institute for Image Data Research, University of Northumbria, Newcastle, NE1 8ST, UK

    John P. Eakins

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© 2002 Springer-Verlag Berlin Heidelberg

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Orriols, X., Binefa, X. (2002). Online Bayesian Video Summarization and Linking. In: Lew, M.S., Sebe, N., Eakins, J.P. (eds) Image and Video Retrieval. CIVR 2002. Lecture Notes in Computer Science, vol 2383. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45479-9_36

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  • DOI: https://doi.org/10.1007/3-540-45479-9_36

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-43899-1

  • Online ISBN: 978-3-540-45479-3

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