A Cognitive Model of Figure Segregation

Abstract

When humans look at a complex and ambiguous figure, they divide it into several elemental figures. This human visual characteristic is called figure segregation. There is a problem when constructing a cognitive model for figure segregation. That is, one interpretation is selected by most people for some figures, and several interpretations are selected almost equally for other figures. This paper discusses the deciding selection frequency problem. First, a geometrical function is introduced for describing line figures. Next, several Gestalt features (such as symmetry, continuity, etc) are defined using the function. Then, by applying linear multiple regression analysis, the characteristic value of each interpretation is obtained, and the selection frequency is calculated. The results of a psychological experiment show that the model proposed here can simulate human visual perception in figure segregation fairly well.