Manifold Next Event Estimation

We present manifold next event estimation (MNEE), a specialised technique for Monte Carlo light transport simulation to render refractive caustics by connecting surfaces to light sources (next event estimation) across transmissive interfaces. We employ correlated sampling by means of a perturbation...

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Vydáno v:Computer graphics forum Ročník 34; číslo 4; s. 87 - 97
Hlavní autoři: Hanika, Johannes, Droske, Marc, Fascione, Luca
Médium: Journal Article
Jazyk:angličtina
Vydáno: Oxford Blackwell Publishing Ltd 01.07.2015
Témata:
Categories and Subject Descriptors (according to ACM CCS)
Caustics
Computer graphics
Computer simulation
Construction
I.3.7 [Computer Graphics]: Three-Dimensional Graphics and Realism-Raytracing
Importance sampling
Manifolds
Monte Carlo methods
Monte Carlo simulation
Sampling
Studies
Weight reduction
United States > US
ISSN:0167-7055, 1467-8659
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Shrnutí:We present manifold next event estimation (MNEE), a specialised technique for Monte Carlo light transport simulation to render refractive caustics by connecting surfaces to light sources (next event estimation) across transmissive interfaces. We employ correlated sampling by means of a perturbation strategy to explore all half vectors in the case of rough transmission while remaining outside of the context of Markov chain Monte Carlo, improving temporal stability. MNEE builds on differential geometry and manifold walks. It is very lightweight in its memory requirements, as it does not use light caching methods such as photon maps or importance sampling records. The method integrates seamlessly with existing Monte Carlo estimators via multiple importance sampling.
Bibliografie:istex:25051F3A1544BA249822EC51033B89D9B009CCF4
Supporting Information
ark:/67375/WNG-LB39B57X-2
ArticleID:CGF12681
SourceType-Scholarly Journals-1
ObjectType-Feature-1
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ISSN:0167-7055
1467-8659
DOI:10.1111/cgf.12681