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Natural statistics and human perception of shape and gloss

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If you have a question about this talk, please contact John Mollon.

The host for this talk is Dr Andrew Welchman

Recovering the 3D shape and reflectance of objects in our environment from 2D retinal images is a highly complex and ill-posed problem. The effects of object shape, reflectance and illumination structure are confounded in the image. To perform well in natural environments the human visual system must (i) use all available information, (ii) jointly estimate the generative variables and (iii) exploit knowledge of the statistics of the environment. Here I describe studies that indicate that observers use not just vision, but also touch information when estimating surface gloss, as well as recent work showing that we jointly estimate shape and reflectance. I will also introduce the Southampton-York Natural Scenes dataset (SYNS: The SYNS dataset includes scenes surveyed at random locations within diverse indoor and outdoor environment categories. Each survey consists of (a) spherical LiDAR range data (b) high-dynamic range spherical imagery and© a panorama of stereo image pairs.

This talk is part of the Craik Club series.

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