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Alive Fishes Species Characterization from Video Sequences

  • Dahbia Semani
  • Christophe Saint-Jean
  • Carl Frélicot
  • Thierry Bouwmans
  • Pierre Courtellemont
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2396)

Abstract

This article presents a method suitable for the characterization of fishes evolving in a basin. It is based on the analysis of video sequences obtained from a fixed camera. One of the main difficulties of analyzing natural scenes acquired from an aquatic environment is the variability of illumination. This disturbs every phase of the whole process. We propose to make each task more robust. In particular, we propose to use a clustering method allowing to provide species parameters estimates that are less sensitive to outliers.

Keywords

Video Sequence Global Cluster Deformable Object Statistical Pattern Recognition Species Characterization 
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 2002

Authors and Affiliations

  • Dahbia Semani
    • 1
  • Christophe Saint-Jean
    • 1
  • Carl Frélicot
    • 1
  • Thierry Bouwmans
    • 1
  • Pierre Courtellemont
    • 1
  1. 1.L3I - UPRESLa Rochelle Cedex 1France

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