Speeding-up Graphical Model Optimization via a Coarse-to-fine Cascade of Pruning Classifiers.
Bruno ConejoNikos KomodakisSébastien LeprinceJean-Philippe AvouacPublished in: CoRR (2014)
Keyphrases
- coarse to fine
- graphical models
- belief propagation
- multiscale
- multiresolution
- probabilistic model
- probabilistic inference
- random variables
- probabilistic graphical models
- approximate inference
- object detection
- convolutional network
- image registration
- hierarchical segmentation
- bayesian networks
- conditional random fields
- dynamic programming
- markov networks
- exact inference
- structure learning
- belief networks
- factor graphs
- training data
- conditional dependencies
- gaussian graphical models
- deformable surface model
- search space
- feature selection
- graph structure
- message passing
- weak classifiers
- support vector
- training samples
- active contours
- markov random field
- training set
- image processing
- computer vision
- machine learning