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Abstract

In evaluating a hierarchy of segmentations H of an image by ground truth G, which can be partitions of the space or sets, we look for the optimal partition in H that “fits” G best. Two energies on partial partitions express the proximity from H to G, and G to H. They derive from a local version of the Hausdorff distance. Then the problem amounts to finding the cut of the hierarchy which minimizes the said energy. This cuts provide global similarity measures of precision and recall. This allows to contrast two input hierarchies with respect to the G, and also to describe how to compose energies from different ground truths. Results are demonstrated over the Berkeley database.

Keywords

Distance Function Ground Truth Partial Partition Minimum Span Forest Global Consistency Error 
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 2013

Authors and Affiliations

  • Bangalore Ravi Kiran
    • 1
  • Jean Serra
    • 1
  1. 1.Laboratoire d’Informatique Gaspard-Monge, A3SI, ESIEEUniversité Paris-EstFrance

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