Model Selection Criterion Applied to Visual Perception

Model selection, which means selecting a suitable model from a class of plausible candidate models to explain the given data, is important in almost every field of scientific research including visual perception process. In fact, model selection bears a striking similarity to visual perception in view of inverse problem, and model selection is an all-pervading problem in visual perception. This paper elucidates the relation between model selection and visual perception and shows an illustrative application example of quantitative characterization of Gestalt cues for contour grouping by using a new information geometric model selection criterion IGMSC. The experimental results show that applying model selection criterion in visual perception is helpful to solve the ill-posedness of perception problem and determine the suitable quantitative model