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Ennio Mingolla, Levin Kuhlmann, Stephen Grossberg; A laminar cortical model of 3D shape-from-texture: spatial-scale filtering, cooperative-competitive grouping, and surface filling-in. Journal of Vision 2004;4(8):472. doi: 10.1167/4.8.472.
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© ARVO (1962-2015); The Authors (2016-present)
A laminar cortical model of interactions within cortical areas V1, V2, and V4 is proposed to explain how the brain converts a textured 2D image into a representation of 3D shape. The percepts of a variety of benchmark “shape from texture” stimuli, such as images from Todd and Oomes (2002, Vis. Res., 42, 837), are simulated. At least two basic problems must be solved to realize this goal: (1) Transform spatially discrete 2D texture elements into a spatially smooth surface representation of 3D shape. (2) Explain how changes in the statistical properties of texture elements across space induce the perceived 3D shape of this surface representation. In the model, multiple spatial-scale sensitive filters process the 2D image. Several filters can respond to the same texture features, but to different degrees and in different ways. The model clarifies how this ambiguous representation of shape is disambiguated using cooperative and competitive boundary interactions that carry out scale-sensitive perceptual grouping within and between filter scales. Of particular interest are across-scale interactions that realize a near-to-far depth asymmetry, which has elsewhere been used in FACADE theory to explain data about figure-ground separation. These processes take place within multiple, depth-selective boundary representations before the boundary representations regulate the filling-in of a smooth 3D surface representation.
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