DocumentCode
3016825
Title
P3 & Beyond: Solving Energies with Higher Order Cliques
Author
Kohli, Pushmeet ; Kumar, M. Pawan ; Torr, Philip H S
Author_Institution
Oxford Brookes Univ., Oxford
fYear
2007
fDate
17-22 June 2007
Firstpage
1
Lastpage
8
Abstract
In this paper we extend the class of energy functions for which the optimal alpha-expansion and alphabeta-swap moves can be computed in polynomial time. Specifically, we introduce a class of higher order clique potentials and show that the expansion and swap moves for any energy function composed of these potentials can be found by minimizing a submodular function. We also show that for a subset of these potentials, the optimal move can be found by solving an st-mincut problem. We refer to this subset as the P3 Potts model. Our results enable the use of powerful move making algorithms i.e. alpha-expansion and alphabeta-swap for minimization of energy functions involving higher order cliques. Such functions have the capability of modelling the rich statistics of natural scenes and can be used for many applications in computer vision. We demonstrate their use on one such application i.e. the texture based video segmentation problem.
Keywords
computational complexity; computer vision; graph theory; image segmentation; video signal processing; P3 Potts model; alpha-expansion; alphabeta-swap moves; computer vision; energy functions minimization; higher order clique potential; natural scenes; polynomial time; st-mincut problem; video segmentation problem; Application software; Approximation methods; Computer vision; Higher order statistics; Inference algorithms; Labeling; Layout; Minimization methods; Polynomials; Random variables;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Vision and Pattern Recognition, 2007. CVPR '07. IEEE Conference on
Conference_Location
Minneapolis, MN
ISSN
1063-6919
Print_ISBN
1-4244-1179-3
Electronic_ISBN
1063-6919
Type
conf
DOI
10.1109/CVPR.2007.383204
Filename
4270229
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