The spectrum of patterns should be continuous . Thus models for texture up to geometry should form a nested family and be compatible. In statistical mechanics, a stochastic pattern is modeled by a Gibbs distribution with potentials defined on a neighborhood system. Models of visual patterns should be learned from observations. We must use generative models which naturally reflect the hierarchic organization of particles.
Descriptive models are the precursors of generative model.
Descriptive models can be learned from a minimax entropy learning theory, and generative models are learned through EM-type algorithm and it integrates the minimax entropy learning. An integrated learning paradigm. Stochastic line, curve, and graph processes.