Computational model for neural representation of multiple disparities.

Abstract

It has been known that the visual system can detect more than one disparity and/or motion direction at the same region in the image. These multiple (or transparent) surfaces can be perceived when, for example, we are looking scenes through a glass. However, many conventional models cannot deal with these multiple surfaces. The present paper investigates the neural encoding and decoding of multiple disparities with the binocular energy model, which is known as a biologically plausible model. Based on the analysis of the response of the energy model to multiple disparities, the present paper proposes a stereo model that can detect disparities of two overlapping surfaces.