Climbing: a unified approach for global constraints on hierarchical segmentation

Authors:
Bangalore Ravi Kiran;Jean Serra;Jean Cousty
Affiliations:
Laboratoire d'Informatique Gaspard-Monge, A3SI, ESIEE, Université Paris-Est, France;Laboratoire d'Informatique Gaspard-Monge, A3SI, ESIEE, Université Paris-Est, France;Laboratoire d'Informatique Gaspard-Monge, A3SI, ESIEE, Université Paris-Est, France
Venue:
ECCV'12 Proceedings of the 12th international conference on Computer Vision - Volume Part III
Year:
2012

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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.