Submodularity beyond submodular energies: coupling edges in graph cuts

Jegelka, S; Bilmes, J

doi:10.1109/CVPR.2011.5995589

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Submodularity beyond submodular energies: coupling edges in graph cuts

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Jegelka, S
Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Citation

Jegelka, S., & Bilmes, J. (2011). Submodularity beyond submodular energies: coupling edges in graph cuts. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2011) (pp. 1897-1904). Piscataway, NJ, USA: IEEE.

Cite as: https://hdl.handle.net/11858/00-001M-0000-0013-BB84-4

Abstract

We propose a new family of non-submodular global energy functions that still use submodularity internally to couple edges in a graph cut. We show it is possible to develop an efﬁcient approximation algorithm that, thanks to the internal submodularity, can use standard graph cuts as a subroutine. We demonstrate the advantages of edge coupling in a natural setting, namely image segmentation. In particular, for ﬁnestructured objects and objects with shading variation, our structured edge coupling leads to signiﬁcant improvements over standard approaches.