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  Submodularity beyond submodular energies: coupling edges in graph cuts

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.

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Jegelka, S1, 2, Author              
Bilmes, J, Author              
Affiliations:
1Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497795              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497794              

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 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.

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 Dates: 2011-06
 Publication Status: Published in print
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 Identifiers: DOI: 10.1109/CVPR.2011.5995589
BibTex Citekey: JegelkaB2011
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Title: IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2011)
Place of Event: Colorado Springs, CO, USA
Start-/End Date: 2011-06-20 - 2011-06-25

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Title: IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2011)
Source Genre: Proceedings
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Publ. Info: Piscataway, NJ, USA : IEEE
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 1897 - 1904 Identifier: ISBN: 978-1-4577-0394-2