A Unified Manifold Framework for Efficient BRDF Sampling based on Parametric Mixture Models

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F18%3A10386558" target="_blank" >RIV/00216208:11320/18:10386558 - isvavai.cz</a>

Výsledek na webu

<a href="https://cgg.mff.cuni.cz/~jaroslav/papers/2018-brdfmanifold/2018-herholz-brdfmanifold-paper.pdf" target="_blank" >https://cgg.mff.cuni.cz/~jaroslav/papers/2018-brdfmanifold/2018-herholz-brdfmanifold-paper.pdf</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.2312/sre.20181171" target="_blank" >10.2312/sre.20181171</a>

Jazyk výsledku

angličtina

Název v původním jazyce

A Unified Manifold Framework for Efficient BRDF Sampling based on Parametric Mixture Models

Popis výsledku v původním jazyce

VirtuallyallexistinganalyticBRDFmodelsarebuiltfrommultiplefunctionalcomponents(e.g.,Fresnelterm,normaldistribution function, etc.). This makes accurate importance sampling of the full model challenging, and so current solutions only cover a subset of the model&apos;s components. This leads to sub-optimal or even invalid proposed directional samples, which can negatively impact the efficiency of light transport solvers based on Monte Carlo integration. To overcome this problem, we propose a unified BRDF sampling strategy based on parametric mixture models (PMMs). We show that for a given BRDF, the parameters of the associated PMM can be defined in smooth manifold spaces, which can be compactly represented using multivariate B-Splines. These manifolds are defined in the parameter space of the BRDF and allow for arbitrary, continuous queries of the PMM representation for varying BRDF parameters, which further enables importance sampling for spatially varying BRDFs. Our representation is not limited to analytic BRDF models, but can also be used for sampling measured BRDF data. The resulting manifold framework enables accurate and efficient BRDF importance sampling with very small approximation errors.

Název v anglickém jazyce

A Unified Manifold Framework for Efficient BRDF Sampling based on Parametric Mixture Models

Popis výsledku anglicky

VirtuallyallexistinganalyticBRDFmodelsarebuiltfrommultiplefunctionalcomponents(e.g.,Fresnelterm,normaldistribution function, etc.). This makes accurate importance sampling of the full model challenging, and so current solutions only cover a subset of the model&apos;s components. This leads to sub-optimal or even invalid proposed directional samples, which can negatively impact the efficiency of light transport solvers based on Monte Carlo integration. To overcome this problem, we propose a unified BRDF sampling strategy based on parametric mixture models (PMMs). We show that for a given BRDF, the parameters of the associated PMM can be defined in smooth manifold spaces, which can be compactly represented using multivariate B-Splines. These manifolds are defined in the parameter space of the BRDF and allow for arbitrary, continuous queries of the PMM representation for varying BRDF parameters, which further enables importance sampling for spatially varying BRDFs. Our representation is not limited to analytic BRDF models, but can also be used for sampling measured BRDF data. The resulting manifold framework enables accurate and efficient BRDF importance sampling with very small approximation errors.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

<a href="/cs/project/GA16-18964S" target="_blank" >GA16-18964S: Adaptivní vzorkování a metody Markov chain Monte Carlo v simulaci transportu světla</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2018

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Eurographics Symposium on Rendering - Experimental Ideas &amp; Implementations

ISBN

978-3-03868-068-0

ISSN

1727-3463

e-ISSN

neuvedeno

Počet stran výsledku

12

Strana od-do

—

Název nakladatele

The Eurographics Association

Místo vydání

Switzerland

Místo konání akce

Karlsruhe, Germany

Datum konání akce

2. 7. 2018

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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