1.2

Markov Random Fields and Gibbs Distributions

Markov random fields theory is a branch of probability theory for analyzing the spatial or contextual dependencies of physical phenomena. It is used in visual labeling to establish probabilistic distributions of interacting labels.   This section introduces notations and results relevant to vision.

• 1.2.1 Neighborhood System and Cliques
• 1.2.2 Markov Random Fields
• 1.2.3 Gibbs Random Fields
• 1.2.4 Markov-Gibbs Equivalence
• 1.2.5 Normalized and Canonical Forms