Image constraints on the perception of surfaces and materials

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Humans visually perceive objects that vary in 3D shape, colour, sheen, and opacity, but understanding how this information is recovered from the images seen remains a mystery. The brain must exploit constraints on the way images are formed through the interaction of light with different surface properties. This project aims to identify image constraints that the brain measures to infer this material diversity. This will advance understandings of computational processes underlying material perception. It will create efficient innovations in image-based pattern recognition algorithms used for commercial and everyday applications, such as quality sorting of fresh produce, and monitoring driver performance in wet weather to reduce errors.