A comprehensive physical model for light reflection
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Predicting reflectance functions from complex surfaces
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Non-linear approximation of reflectance functions
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A Reflectance Model for Computer Graphics
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Homomorphic factorization of BRDFs for high-performance rendering
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An anisotropic BRDF model for fitting and Monte Carlo rendering
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Inverse bi-scale material design
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BTF based material representations: current challenges
MAM '13 Proceedings of the Eurographics 2013 Workshop on Material Appearance Modeling: Issues and Acquisition
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We present a generative model for isotropic bidirectional reflectance distribution functions (BRDFs) based on acquired reflectance data. Instead of using analytical reflectance models, we represent each BRDF as a dense set of measurements. This allows us to interpolate and extrapolate in the space of acquired BRDFs to create new BRDFs. We treat each acquired BRDF as a single high-dimensional vector taken from a space of all possible BRDFs. We apply both linear (subspace) and non-linear (manifold) dimensionality reduction tools in an effort to discover a lower-dimensional representation that characterizes our measurements. We let users define perceptually meaningful parametrization directions to navigate in the reduced-dimension BRDF space. On the low-dimensional manifold, movement along these directions produces novel but valid BRDFs.