Solving da Vinci stereopsis with depth-edge-selective V2 cells.

We propose a new model for da Vinci stereopsis based on a coarse-to-fine disparity energy computation in V1 and disparity-boundary-selective units in V2. Unlike previous work, our model contains only binocular cells, relies on distributed representations of disparity, and has a simple V1-to-V2 feedforward structure. We demonstrate with random-dot stereograms that the V2 stage of our model is able to determine the location and the eye-of-origin of monocularly occluded regions, and improve disparity map computation. We also examine a few related issues. First, we argue that since monocular regions are binocularly defined, they cannot generally be detected by monocular cells. Second, we show that our coarse-to-fine V1 model for conventional stereopsis explains double matching in Panum's limiting case. This provides computational support to the notion that the perceived depth of a monocular bar next to a binocular rectangle may not be da Vinci stereopsis per se [Gillam, B., Cook, M., & Blackburn, S. (2003). Monocular discs in the occlusion zones of binocular surfaces do not have quantitative depth--a comparison with Panum's limiting case. Perception 32, 1009-1019.]. Third, we demonstrate that some stimuli previously deemed invalid have simple, valid geometric interpretations. Our work suggests that studies of da Vinci stereopsis should focus on stimuli more general than the bar-and-rectangle type and that disparity-boundary-selective V2 cells may provide a simple physiological mechanism for da Vinci stereopsis.