Class-Specific, Top-Down Segmentation

  • Eran Borenstein
  • Shimon Ullman
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2351)


In this paper we present a novel class-based segmentation method, which is guided by a stored representation of the shape of objects within a general class (such as horse images). The approach is different from bottom-up segmentation methods that primarily use the continuity of grey-level, texture, and bounding contours. We show that the method leads to markedly improved segmentation results and can deal with significant variation in shape and varying backgrounds. We discuss the relative merits of class-specific and general image-based segmentation methods and suggest how they can be usefully combined.


Grouping and segmentation Figure-ground Top-down processing Object classification 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Eran Borenstein
    • 1
  • Shimon Ullman
    • 1
  1. 1.Dept. of Computer Science and Applied MathThe Weizmann Institute of ScienceRehovotIsrael

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