Stochastic completion fields: A neural model of illusory contour shape and salience

Describes an algorithm- and representation-level theory of illusory contour shape and salience. Unlike previous theories, the model is derived from a single assumption: that the prior probability distribution of boundary completion shape can be modeled by a random walk. The model does not use numerical relaxation or other explicit minimization, but instead relies on the fact that the probability that a particle following a random walk will pass through a given position, and orientation on a path joining 2 boundary fragments can be computed directly as the product of 2 vector-field convolutions. It is shown that for the random walk defined, the maximum likelihood paths are curves of least energy, that is, on average, random walks follow paths commonly assumed to model the shape of illusory contours. A computer model is demonstrated on numerous illusory contour stimuli from the literature. (PsycINFO Database Record (c) 2012 APA, all rights reserved)