Pascal Barla

Abstract Recognizing materials and their properties visually is vital for successful interactions with our environment, from avoiding slippery floors to handling fragile objects. Yet there is no simple mapping of retinal image intensities to physical properties. Here, we investigated what image information drives material perception by collecting human psychophysical judgements about complex glossy objects.

If the estimation of viscosity proceeds hierarchically—through a weighted combination of midlevel features describing dynamic 3D shape properties—it should be possible to identify such features and use them to predict perceived viscosity across variations in other scene variables.