A Coarse-and-Fine Bayesian Belief Propagation for Correspondence Problems in Computer Vision.
Preeyakorn TipwaiSuthep MadarasmiPublished in: MICAI (2007)
Keyphrases
- problems in computer vision
- belief propagation
- energy minimization
- energy function
- graph cuts
- coarse to fine
- graphical models
- markov random field
- message passing
- stereo matching
- approximate inference
- scene reconstruction
- pairwise
- loopy belief propagation
- pose estimation
- fixed point
- bayesian networks
- markov networks
- computer vision
- free energy
- stereo correspondence
- factor graphs
- posterior distribution
- bayesian inference
- point correspondences
- image matching
- image segmentation
- posterior probability
- active contours
- dynamic programming
- maximum a posteriori
- maximum likelihood
- probability distribution
- multiscale
- high quality
- max product
- machine learning
- probabilistic inference
- conditional random fields
- level set