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» Statistical Priors for Efficient Combinatorial Optimization ...
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ECCV
2006
Springer
14 years 6 months ago
Statistical Priors for Efficient Combinatorial Optimization Via Graph Cuts
Abstract. Bayesian inference provides a powerful framework to optimally integrate statistically learned prior knowledge into numerous computer vision algorithms. While the Bayesian...
Daniel Cremers, Leo Grady
CVPR
2005
IEEE
14 years 6 months ago
Corrected Laplacians: Closer Cuts and Segmentation with Shape Priors
We optimize over the set of corrected laplacians (CL) associated with a weighted graph to improve the average case normalized cut (NCut) of a graph. Unlike edge-relaxation SDPs, o...
David Tolliver, Gary L. Miller, Robert T. Collins
EMMCVPR
2007
Springer
13 years 8 months ago
Efficient Shape Matching Via Graph Cuts
Abstract. Meaningful notions of distance between planar shapes typically involve the computation of a correspondence between points on one shape and points on the other. To determi...
Frank R. Schmidt, Eno Töppe, Daniel Cremers, ...
IJCV
2006
299views more  IJCV 2006»
13 years 4 months ago
Graph Cuts and Efficient N-D Image Segmentation
Combinatorial graph cut algorithms have been successfully applied to a wide range of problems in vision and graphics. This paper focusses on possibly the simplest application of gr...
Yuri Boykov, Gareth Funka-Lea
IBPRIA
2007
Springer
13 years 10 months ago
Bayesian Oil Spill Segmentation of SAR Images Via Graph Cuts
Abstract. This paper extends and generalizes the Bayesian semisupervised segmentation algorithm [1] for oil spill detection using SAR images. In the base algorithm on which we buil...
Sónia Pelizzari, José M. Bioucas-Dia...