RECONSIDERING THE ROLE OF STRUCTURE IN VISION

Publisher Summary This chapter focuses on the role of structure in mental representations and visual object recognition. A match between an incoming image and a stored image is registered based on global similarity across a homogeneous input space. One of the best pieces of evidence for structural models in visual recognition is text reading. Recent empirical evidence suggests that word recognition depends on identifying letters as opposed to recognizing the word holistically as a single pattern. Structural accounts of recognition are those in which the identification of a visual object depends on both a set of features and the relations between those features within some representational space. The primate visual system is clearly able to extract and represent structural information, for example, spatial relations, at a wide variety of scales. The computational utility of compositional structure has been considered in depth with regard to a number of cognitive domains, and in particular, with respect to language. A compositional architecture allows you to generate arbitrary constructions based on a limited set of starting units, a property referred to as productivity.