English
 
User Manual Privacy Policy Disclaimer Contact us
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT

Released

Conference Paper

Submodularity beyond submodular energies: coupling edges in graph cuts

MPS-Authors
/persons/resource/persons83994

Jegelka,  S.
Dept. Empirical Inference, Max Planck Institute for Intelligent Systems, Max Planck Society;

/persons/resource/persons75286

Bilmes,  J.
Dept. Empirical Inference, Max Planck Institute for Intelligent Systems, Max Planck Society;

External Ressource
No external resources are shared
Fulltext (public)
There are no public fulltexts stored in PuRe
Supplementary Material (public)
There is no public supplementary material available
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).


Cite as: http://hdl.handle.net/11858/00-001M-0000-0010-75C1-1
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.