Submodularity beyond submodular energies: coupling edges in graph cuts

Jegelka, S; Bilmes, J

doi:10.1109/CVPR.2011.5995589

アイテム詳細

登録内容を編集ファイル形式で保存

一時保存へ追加

タグ情報を表示リリース履歴を表示詳細要約

公開

会議論文

Submodularity beyond submodular energies: coupling edges in graph cuts

MPS-Authors

/persons/resource/persons83994

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

External Resource

https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5995589
(出版社版)

Fulltext (restricted access)

There are currently no full texts shared for your IP range.

フルテキスト (公開)

公開されているフルテキストはありません

付随資料 (公開)

There is no public supplementary material available

引用

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.

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

要旨

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.