Abstract
There is an explanatory gap between the simple local image measurements of early vision, and the complex perceptual inferences involved in estimating object properties such as surface reflectance and 3D shape. The main purpose of my presentation will be to discuss how populations of filters tuned to different orientations and spatial frequencies can be ‘put to good use’ in the estimation of 3D shape. I'll show how shading, highlights and texture patterns on 3D surfaces lead to highly distinctive signatures in the local image statistics, which the visual system could use in 3D shape estimation. I will discuss how the spatial organization of these measurements provides additional information, and argue that a common front end can explain both similarities and differences between various monocular cues. I'll also present a number of 3D shape illusions and show how these can be predicted by image statistics, suggesting that human vision does indeed make use of these measurements.