Material Appearance Modeling
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Browsing Material Appearance Modeling by Subject "I.2.10 [Artificial Intelligence]"
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Item Exploring Material Recognition for Estimating Reflectance and Illumination From a Single Image(The Eurographics Association, 2016) Weinmann, Michael; Klein, Reinhard; Reinhard Klein and Holly RushmeierIn this paper, we propose a novel approach for recovering illumination and reflectance from a single image. Our approach relies on the assumption that the surface geometry has already been reconstructed and a-priori knowledge in form of a database of digital material models is available. The first step of our technique consists in recognizing the respective material in the image using synthesized training data based on the given material database. Subsequently, the illumination conditions are estimated based on the recognized material and the surface geometry. Using this novel strategy we demonstrate that reflectance and illumination can be estimated reliably for several materials that are beyond simple Lambertian surface reflectance behavior because of exhibiting mesoscopic effects such as interreflections and shadows.Item A Short Survey on Optical Material Recognition(The Eurographics Association, 2015) Weinmann, M.; Klein, R.; Reinhard Klein and Holly RushmeierThe complexity of visual material appearance as observed in the huge variation in material appearance under different viewing and illumination conditions makes material recognition a highly challenging task. In the scope of this paper, we discuss the facts that make material appearance that complex and provide a survey on technical achievements towards a reliable material recognition that have been presented in the literature so far. In addition, we discuss still open challenges that might be in the focus of future research.