A computational theory of da Vinci stereopsis.

Abstract

In binocular vision, occlusion of one object by another gives rise to monocular occlusions—regions visible only in one eye. Although binocular disparities cannot be computed for these regions, monocular occlusions can be precisely localized in depth and can induce the perception of illusory occluding surfaces. The phenomenon of depth perception from monocular occlusions, known as da Vinci stereopsis, is intriguing, but its mechanisms are not well understood. We first propose a theory of the mechanisms underlying da Vinci stereopsis that is based on the psychophysical and computational literature on monocular occlusions. It postulates, among other principles, that monocular areas are detected explicitly, and depth from occlusions is calculated based on constraints imposed by occlusion geometry. Next, we describe a biologically inspired computational model based on this theory that successfully reconstructs depth in a large range of stimuli and produces results similar to those described in the psychophysical literature. These results demonstrate that the proposed neural architecture could underpin da Vinci stereopsis and other stereoscopic percepts.