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» Statistical Priors for Efficient Combinatorial Optimization ...
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ECCV
2006
Springer
14 years 9 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 9 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 11 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 7 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
14 years 1 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...