Browsing MAM2018: Eurographics Workshop on Material Appearance Modeling by Title
Now showing items 7-12 of 12
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On the Advancement of BTF Measurement on Site
(The Eurographics Association, 2018)We present our progress to the on-site measurement of the spatially varying surface reflectance represented by bidirectional texture function (BTF). This requires a physical realization of a portable instrument that can ... -
Perception of Car Shape Orientation and Anisotropy Alignment
(The Eurographics Association, 2018)The color designers are used to introduce customized product design, visually communicating the unique impression of a car. They always carefully observe harmony of color and body shape to obtain desired visual impression. ... -
A Simple Diffuse Fluorescent BBRRDF Model
(The Eurographics Association, 2018)Fluorescence - the effect of a photon being absorbed at one wavelength and re-emitted at another - is present in many common materials such as clothes and paper. Yet there has been little research in rendering or modeling ... -
Towards a Principled Kernel Prediction for Spatially Varying BSSRDFs
(The Eurographics Association, 2018)While the modeling of sub-surface translucency using homogeneous BSSRDFs is an established industry standard, applying the same approach to heterogeneous materials is predominantly heuristical. We propose a more principled ... -
Towards Physically Based Material Appearance in the Thermal Infrared Spectrum: A Short Survey
(The Eurographics Association, 2018)In the context of photorealistic rendering, global illumination mainly relies on material models from the visible spectrum, whereas thermal infrared signatures receive only little attention. This paper outlines physical ... -
Towards Practical Rendering of Fiber-Level Cloth Appearance Models
(The Eurographics Association, 2018)Accurate representation of realistic cloth appearance is of high importance in many industry fields such as entertainment and textile design. However, microstructure of fibers and their optical properties generate very ...