Shape from specularities: computation and psychophysics

Abstract

Images of artificial and natural scenes typically contain many ‘specularities’ generated by mirror-like reflection from glossy surfaces. Until fairly recently computational models of visual processes have tended to regard specularities as obscuring underlying scene structure. Mathematical modelling shows that, on the contrary, they are rich in local geometric information. Recent psychophysical findings support the notion that the brain can apply that information. Our results concern the inference of 3D structure from 2D shaded images of glossy surfaces. Stereoscopically viewed highlights or ‘specularities’ are found to serve as cues for 3D local surface-geometry.