Perceptual Grouping of Contour Segments Using Markov Random Fields

Abstract

The aim of this work is to exploit regular structure in a scene by using the gestalt laws of perception in the field of computer vision. The statistical result of a hand labelled training set is employed to derive "Areas of perceptual attentiveness". Grouping hypotheses are thus generated based on local evidence. To judge these hypotheses in a more global context a Markov random field is used. The approach is contour-based and different types of grouping hypotheses define a hierarchy according to their growing complexity.