2014
DOI: 10.1145/2601097.2601186
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Discrete stochastic microfacet models

Abstract: Figure 1: Left: fancy pair of women's dress shoes with a glittery finish modeled using our discrete microfacet BRDF. Right: Christmas ornaments illustrating a range of model parameters including different particle counts, surface roughness, and anisotropy. AbstractThis paper investigates rendering glittery surfaces, ones which exhibit shifting random patterns of glints as the surface or viewer moves. It applies both to dramatically glittery surfaces that contain mirror-like flakes and also to rough surfaces th… Show more

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Cited by 71 publications
(93 citation statements)
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“…[Jakob et al 2014] is concurrent work that also addresses the problem of glinty surfaces, using a stochastic approach. Rather than work from a normal map, that method models the surface as a procedural random collection of specular flakes that occur according to a particular normal distribution.…”
Section: Related Workmentioning
confidence: 99%
“…[Jakob et al 2014] is concurrent work that also addresses the problem of glinty surfaces, using a stochastic approach. Rather than work from a normal map, that method models the surface as a procedural random collection of specular flakes that occur according to a particular normal distribution.…”
Section: Related Workmentioning
confidence: 99%
“…Jakob et al [JHY∗14] use a stochastic approach to simulate glittery effects using a statistical distribution of tiny, mirror‐like flakes. This method is memory‐efficient and temporally stable in animation.…”
Section: Related Workmentioning
confidence: 99%
“…This concept has also been tested successfully in real-time rendering [173]. Improved version, that includes discrete stochastic for random spatial variation of BRDF, is presented recently [174]. In order to solve antialiasing of surfaces using high-level of details using microfacet models at all scales Dupuy et al proposed Linear Efficient Antialiased Displacement and Reflectance (LEADR) Mapping [175].…”
Section: Bipv Facade Module To Building Scalementioning
confidence: 99%