title: RAP: a new framework for visual categorization.
abstract: Cognitive science might almost be defined as several disciplines communicating their different perspectives on the mind, the common object of study. However, domain-specific concepts and techniques can prevent, rather than foster, a communication of viewpoints. In this article, we develop a new framework for visual categorization in which the interaction between Represented (R) information and Available (A) information determine the Potent (P) information (symbolically, R ? A approximately P). We argue and illustrate that this framework helps to establish a common language to articulate issues common to low-, mid-, and high-level vision. More importantly, we present new techniques with which to visualize the so-far elusive constructs of representation and potent information.
authors.affiliation: Dépt de Psychologie, Université de Montréal, C. P. 6128, Succ. Centre-ville, Montréal QC, Canada. frederic.gosselin@umontreal.ca
authors.forename: Frédéric
authors.initials: F
authors.lastname: Gosselin
authors.forename: Philippe G
authors.initials: PG
authors.lastname: Schyns