Proceedings of the Annual Meeting of the Cognitive Science Society

Despite the fact that complex visual scenes contain multiple, overlapping objects, people perform object recognition with ease and accuracy. Psychological and neuropsychological data argue for a segmentation process that assists in object recognition by grouping low-level visual features based on which object they belong to. W e review several approaches to segmentation/recognition and argue for a bottom-up segmentation process that is based on feature grouping heuristics. The challenge of this approach is to determine appropriate grouping heuristics. Previously, researchers have hypothesized grouping heuristics and then tested their psychological validity or computational utility. W e suggest a basic principle underlying these heuristics: they are a reflection of the structure of the environment. W e have therefore taken an adaptive approach to the problem of segmentation in which a system, called magic, learns how to group features based on a set of presegmented examples. Whereas traditional grouping principles indicate the conditions under which features should be bound together £is part of the same object, the grouping principles learned by magic also indicate when features should be segregated into different objects. W e describe psychological studies aimed at determining whether limitations of MAGIC correspond to limitations of human visual information processing.