“Proto-rivalry”: how the binocular brain identifies gloss

Abstract

Visually identifying glossy surfaces can be crucial for survival (e.g., ice patches on a road), yet estimating gloss is computationally challenging for both human and machine vision. Here, we demonstrate that human gloss perception exploits some surprisingly simple binocular fusion signals, which are likely available early in visual cortex. In particular, we show that the unusual disparity gradients and vertical offsets produced by reflections create distinctive "proto-rivalrous" (barely fusible) image regions that are a critical indicator of gloss. We find that manipulating the gradients and vertical components of binocular disparities yields predictable changes in material appearance. Removing or occluding proto-rivalrous signals makes surfaces look matte, while artificially adding such signals to images makes them appear glossy. This suggests that the human visual system has internalized the idiosyncratic binocular fusion characteristics of glossy surfaces, providing a straightforward means of estimating surface attributes using low-level image signals.