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Object qualities from image motion
Humans can effortlessly visually sense dynamic physical properties such as viscosity, elasticity, or stiffness and optical properties such as transparency, glossiness, shininess, or roughness. Many critical perceptual judgments, from telling whether fruit is ripe to determining whether the ground is slippery, involve visually estimating such material properties (see Figure). Yet, very little is known about how the brain recognizes materials, even though the problem is likely as important for survival as navigating or recognizing objects.
To fully understand how conscious experience of material quality can arise it is necessary to both, understand what information the visual system extracts from the inherently ambiguous retinal input, and how this information is processed by the brain. This project’s aim is to identify environmental cues signaling surface material quality and to decipher the neural processes by which surface material perception is mediated. The project’s focus is on dynamic cues to material perception, exploring how image motion can convey optical properties of surface material. This will be accomplished by combining behavioral, computational and neuroimaging methods.