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Segmentation of Moving Objects with Information Feedback Between Description Levels

  • M. Rincón
  • E. J. Carmona
  • M. Bachiller
  • E. Folgado
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4528)

Abstract

In real sequences, one of the factors that most negatively affects the segmentation process result is the existence of scene noise. This impairs object segmentation which has to be corrected if we wish to have some minimum guarantees of success in the following tracking or classification stages. In this work we propose a generic knowledge-based model to improve the segmentation process. Specifically, the model uses a decomposition strategy in description levels to enable the feedback of information between adjacent levels. Finally, two case studies are proposed that instantiate the model proposed for detecting humans.

Keywords

Human Model Video Surveillance Segmentation Process Information Feedback Object Level 
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 Berlin Heidelberg 2007

Authors and Affiliations

  • M. Rincón
    • 1
  • E. J. Carmona
    • 1
  • M. Bachiller
    • 1
  • E. Folgado
    • 1
  1. 1.Dpto. de Inteligencia Artificial. ETSI Informatica. UNED., Juan del Rosal 16, 28040 MadridSpain

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