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Climbing: A Unified Approach for Global Constraints on Hierarchical Segmentation

  • Bangalore Ravi Kiran
  • Jean Serra
  • Jean Cousty
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7585)

Abstract

The paper deals with global constraints for hierarchical segmentations. The proposed framework associates, with an input image, a hierarchy of segmentations and an energy, and the subsequent optimization problem. It is the first paper that compiles the different global constraints and unifies them as Climbing energies. The transition from global optimization to local optimization is attained by the h-increasingness property, which allows to compare parent and child partition energies in hierarchies. The laws of composition of such energies are established and examples are given over the Berkeley Dataset for colour and texture segmentation.

Keywords

Global Constraint Texture Segmentation Binary Energy Optimal Segmentation Partial Partition 
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 2012

Authors and Affiliations

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

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