Higher-order Segmentation via Multicuts

Computer Vision and Image Understanding(2016)

引用 58|浏览35
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摘要
•We propose a novel and general formulation for hyper-graph correlation clustering.•Any permutation invariant function can be included into a multicut problem.•We provide a comparison of LP and ILP cutting plane methods and rounding procedures for the multicut problem.•Many sparse Potts models can be solved to global optimality very efficient by the proposed method.•The C++ implementations used in this manuscript is freely available online.
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关键词
Segmentation,Discrete optimization,Multicut,Markov random fields,Higher-order graphical models,Polyhedral combinatorics,Partitioning,Correlation clustering,Global optimality,Image labeling
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