Using Self-Organizing Maps to Support Video Navigation

  • Thomas Bärecke
  • Ewa Kijak
  • Andreas Nürnberger
  • Marcin Detyniecki
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4131)


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. Unlike existing systems, the clustering is based on a growing self-organizing map algorithm. We focus on studying the applicability of SOMs for video navigation support. We ignore the temporal aspect completely during the clustering, but we project the grouped data on an original time bar control afterwards. This complements our interface by 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. Special attention is also given to the interaction possibilities which are hierarchically organized.


Video Content Colour Histogram Shot Boundary Winner Neuron 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.Faculty of Computer ScienceOtto-von-Guericke Universität MagdeburgGermany

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