Gaussian Product Sampling for Rendering Layered Materials

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dc.contributor.authorXia, Mengqi (Mandy)en_US
dc.contributor.authorWalter, Bruceen_US
dc.contributor.authorHery, Christopheen_US
dc.contributor.authorMarschner, Steveen_US
dc.contributor.editorBenes, Bedrich and Hauser, Helwigen_US
dc.date.accessioned2020-05-22T12:24:44Z
dc.date.available2020-05-22T12:24:44Z
dc.date.issued2020
dc.description.abstractTo increase diversity and realism, surface bidirectional scattering distribution functions (BSDFs) are often modelled as consisting of multiple layers, but accurately evaluating layered BSDFs while accounting for all light transport paths is a challenging problem. Recently, Guo . [GHZ18] proposed an accurate and general position‐free Monte Carlo method, but this method introduces variance that leads to longer render time compared to non‐stochastic layered models. We improve the previous work by presenting two new sampling strategies, and . Our new methods better take advantage of the layered structure and reduce variance compared to the conventional approach of sequentially sampling one BSDF at a time. Our strategy importance samples the product of two BSDFs from a pair of adjacent layers. We further generalize this to , which importance samples the product of a chain of three or more BSDFs. In order to compute these products, we developed a new approximate Gaussian representation of individual layer BSDFs. This representation incorporates spatially varying material properties as parameters so that our techniques can support an arbitrary number of textured layers. Compared to previous Monte Carlo layering approaches, our results demonstrate substantial variance reduction in rendering isotropic layered surfaces.en_US
dc.description.number1
dc.description.sectionheadersArticles
dc.description.seriesinformationComputer Graphics Forum
dc.description.volume39
dc.identifier.doi10.1111/cgf.13883
dc.identifier.issn1467-8659
dc.identifier.pages420-435
dc.identifier.urihttps://doi.org/10.1111/cgf.13883
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1111/cgf13883
dc.publisher© 2020 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltden_US
dc.subjectreflectance and shading models
dc.subjectrendering
dc.subject• Computing methodologies → Reflectance modelling
dc.titleGaussian Product Sampling for Rendering Layered Materialsen_US
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