Affiliation:
1. Department of Psychology and Beckman Institute, University of Illinois Urbana-Champaign
2. Faculty of Information Technology and Electrical Engineering, University of Oulu
Abstract
Multiple models of vision propose that perception involves a process of prediction and verification. Here we argue that real-world statistical regularities—representations that, on average, more quickly make contact with meaning—serve as the basis of these predictions. We show that statistically regular images—those, we argue, that more closely match perceptual predictions—are more readily perceived and more efficiently processed than statistically irregular images.