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Video Navigation Based on Self-Organizing Maps

  • Thomas Bärecke
  • Ewa Kijak
  • Andreas Nürnberger
  • Marcin Detyniecki
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4071)

Abstract

Content-based video navigation is an efficient method for browsing video information. A common approach is to cluster shots into groups and visualize them afterwards. In this paper, we present a prototype that follows in general this approach. The clustering ignores temporal information and is based on a growing self-organizing map algorithm. They provide some inherent visualization properties such as similar elements can be found easily in adjacent cells. We focus on studying the applicability of SOMs for video navigation support. We complement our interface with an original time bar control providing – at the same time – an integrated view of time and content based information. The aim is to supply the user with as much information as possible on one single screen, without overwhelming him.

Keywords

Video Content Colour Histogram Winner Neuron Temporal Segmentation Shot Boundary Detection 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Thomas Bärecke
    • 1
  • Ewa Kijak
    • 1
  • Andreas Nürnberger
    • 2
  • Marcin Detyniecki
    • 1
  1. 1.LIP6Université Pierre et Marie CurieParisFrance
  2. 2.IWSOtto-von-Guericke UniversitätMagdeburgGermany

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