Natural scene statistics and visual inference

Tai Sing Lee

Computer Science Department and Center for the Neural Basis of Cognition, Carnegie Mellon University

Recurrent feedback in the visual cortex can potentially be conceptualized as a mechanism for mediating the influence of prior beliefs in a hierarchical Bayesian inference framework. We consider the computational problem of 3D shape inference based on monocular and binocular cues. We present evidence suggesting that neuronal tuning and neuronal interaction in the primary visual cortex encode ecological statistical priors between 3D scene structures and 2D images relevant for 3D inference. These sensitivities, together with evidence on the response dynamics of neurons in the early visual cortex, are consistent with the hierarchical Bayesian perspective on visual processing.