Understanding Visual Categorization from the Use of Information

Understanding Visual Categorization from the Use of Information Lizann Bonnar (LIZANN@PSY.GLA.AC.UK) Philippe G. Schyns (PHILIPPE@PSY.GLA.AC.UK) Frederic Gosselin (GOSSELIF@PSY.GLA.AC.UK) Department of Psychology, University of Glasgow, 58 Hillhead Street, Glasgow, Scotland, G12 8QB Abstract We propose an approach that allows a rigorous understanding of the visual categorization and recognition process without asking direct questions about unobservable memory representations. Our approach builds on the selective use of information and a new method (Gosselin & Schyns, 2000, Bubbles) to depict and measure what this information is. We examine three face recognition tasks (identity, gender, expressive or not) and establish the information responsible for recognition performance. We compare the human use of information to ideal observers confronted to similar tasks. We finally derive a gradient of probability for the allocation of attention to the different regions of the face. Introduction In recent years, most face, object and scene recognition researchers have gathered around a common agenda: to understand the structure of representations in memory. A number of fundamental issues have been articulated, and researchers typically ask questions such as: “Are face, object and scene representations viewpoint- dependent? “ (Hill, Schyns & Akamatsu, 1997; Perrett, Oram & Ashbridge, 1998; Troje & Bulthoff, 1996; Tarr & Pinker, 1989; Bulthoff & Edelman, 1992; Simons & Wang, 1998, among many others); “Are these representations holistic (e.g, view-based, Poggio & Edelman, 1990; Tarr & Pinker, 1991; Ullman, 1998), or made of smaller components? (e.g,, geons, Biederman, 1987; Biederman & Cooper, 1991)”; “Are internal representations complete (e.g., Cutzu & Edelman, 1996), or sparse? (Archambault, O’Donnell & Schyns, 1999; Rensink, O’Regan & Clark, 1997), “two- or three-dimensional? ” (Liu, Knill & Kersten, 1995), “colored or not? ” (Biederman & Ju, 1988; Oliva & Schyns, 2000; Tanaka & Presnell, 1999), “Are they hierarchically organized in memory? ” (Jolicoeur, Gluck & Kosslyn, 1984; Rosch, Mervis, Gray, Johnson & Boyes-Braem, 1976), “Is there a fixed entry point into the hierarchy? ” (Gosselin & Schyns, in press; Tanaka & Taylor, 1991) “Does expertise modify memory representations? ” (Biederman & Shiffrar, 1987; Tanaka & Gauthier, 1998; Schyns & Rodet, 1997) and the entry point to recognition? ” (Tanaka & Taylor, 1991); “What is the format of memory representations, and does it change uniformly across the levels of a hierarchy? ” (Biederman & Gerhardstein, 1995; Jolicoeur, 1990; Tarr & Bulthoff, 1995). To address these complex issues, recognition researchers should be equipped with methodologies of a commensurate power; methodologies that can assign the credit of behavioral performance (e.g., viewpoint- dependence, configural effects, color, speed of categorization, point of entry, expertise and so forth) to specific properties of the representations of visual events in memory. However, the relationship between behavior and representations is tenuous, making representational issues the most difficult to approach experimentally. In this paper, we propose an alternative approach that allows a rigorous understanding of the recognition process, without directly asking questions about unobservable memory representations. Our analysis builds on the selective use of diagnostic information, an important but neglected stage of the recognition process. To recognize an object, people selectively use information from its projection on the retina. This information is not available to conscious experience, but the visual system knows what it is, and how to extract it from the visual array. Our approach interrogates the visual system to determine and to depict the information the system uses to recognize stimuli. The aim of this paper is twofold. At an empirical level, we will use Gosselin and Schyns (2000) Bubbles technique to visualize the information used in three face categorization tasks (identity, gender and expressive or not). Faces are a good stimulus for our demonstrations: their compactness enables a tight control of presentation which limits the spatial extent of useful cues; the familiarity of their categorizations simplifies the experimental procedure which does not require prior learning of multiple categories--most people are “natural” face experts (Bruce, 1994). However, the principles developed with faces also apply to the more general cases of objects and scenes. At a more theoretical level, we will reveal the information used in recognition tasks without asking questions (or even making assumptions) about memory representations. This is nonetheless a powerful approach because the information used encompasses all the visual features that mediate the recognition task at