P3 & Beyond: Move Making Algorithms for Solving Higher Order Functions

被引:67
作者
Kohli, Pushmeet [1 ]
Kumar, M. Pawan [2 ]
Torr, Philip H. S. [3 ]
机构
[1] Microsoft Res, Cambridge CB3 0FB, England
[2] Stanford Univ, Dept Comp Sci, Stanford, CA 94305 USA
[3] Oxford Brookes Univ, Sch Technol, Oxford OX33 1HX, England
基金
英国工程与自然科学研究理事会;
关键词
Energy minimization; higher order MRFs; graph cuts; move making algorithms; MARKOV RANDOM-FIELDS; ENERGY MINIMIZATION; OPTIMIZATION;
D O I
10.1109/TPAMI.2008.217
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper, we extend the class of energy functions for which the optimal alpha-expansion and alpha beta-swap moves can be computed in polynomial time. Specifically, we introduce a novel family 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 P-n Potts model. Our results enable the use of powerful alpha-expansion and alpha beta-swap move making algorithms for minimization of energy functions involving higher order cliques. Such functions have the capability of modeling the rich statistics of natural scenes and can be used for many applications in Computer Vision. We demonstrate their use in one such application, i.e., the texture-based image or video-segmentation problem.
引用
收藏
页码:1645 / 1656
页数:12
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