Veridical Representation of Shape and Texture Changes in Novel 3D Objects

Categorization researchers and, more recently, object recognition researchers have proposed that similarity may offer an organizational principle for the representation of objects in the brain and have demonstrated that such a principle is capable of supporting the distinct tasks of object recognition and categorization. But what is it that makes two objects perceptually similar? And what role does sensory modality play in shaping perceptual similarity? As a first step towards addressing this question, we used computer graphics modeling techniques to create novel, 3D objects that varied parametrically in shape and texture. In a psychophysical experiment, we then asked human subjects to view pairs of objects and rate the similarity between them. We also generated similarity ratings from a set of standard computer vision techniques (based on pixel-wise differences, cross-correlations, edge images, and Gabor jets). Multidimensional scaling (MDS) on the perceptual similarity data revealed that the perceptual representation of both shape and texture changes is veridical; the twodimensional MDS configuration of stimuli closely matches the configuration in shape and texture parameter space. Interestingly, comparisons against computational measures revealed that simple pixel-based and correlation-based similarities were closest to visual similarities. In future experiments, we plan to compare haptic similarity measures to these visual measures in order to examine the role of modality in mediating the effects of shape and texture changes on perceptual similarities