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Statements

Subject Item
n2:RIV%2F00216208%3A11320%2F12%3A10127580%21RIV13-MSM-11320___
rdf:type
n4:Vysledek skos:Concept
rdfs:seeAlso
http://dx.doi.org/10.1111/j.1467-8659.2012.03049.x
dcterms:description
Realistic rendering requires computing the global illumination in the scene, and Monte Carlo integration is the best-known method for doing that. The key to good performance is to carefully select the costly integration samples, which is usually achieved via importance sampling. Unfortunately, visibility is difficult to factor into the importance distribution, which can greatly increase variance in highly occluded scenes with complex illumination. In this paper, we present importance caching - a novel approach that selects those samples with a distribution that includes visibility, while maintaining efficiency by exploiting illumination smoothness. At a sparse set of locations in the scene, we construct and cache several types of probability distributions with respect to a set of virtual point lights (VPLs), which notably include visibility. Each distribution type is optimized for a specific lighting condition. For every shading point, we then borrow the distributions from nearby cached locations and use them for VPL sampling, avoiding additional bias. A novel multiple importance sampling framework finally combines the many estimators. In highly occluded scenes, where visibility is a major source of variance in the incident radiance, our approach can reduce variance by more than an order of magnitude. Even in such complex scenes we can obtain accurate and low noise previews with full global illumination in a couple of seconds on a single mid-range CPU. Realistic rendering requires computing the global illumination in the scene, and Monte Carlo integration is the best-known method for doing that. The key to good performance is to carefully select the costly integration samples, which is usually achieved via importance sampling. Unfortunately, visibility is difficult to factor into the importance distribution, which can greatly increase variance in highly occluded scenes with complex illumination. In this paper, we present importance caching - a novel approach that selects those samples with a distribution that includes visibility, while maintaining efficiency by exploiting illumination smoothness. At a sparse set of locations in the scene, we construct and cache several types of probability distributions with respect to a set of virtual point lights (VPLs), which notably include visibility. Each distribution type is optimized for a specific lighting condition. For every shading point, we then borrow the distributions from nearby cached locations and use them for VPL sampling, avoiding additional bias. A novel multiple importance sampling framework finally combines the many estimators. In highly occluded scenes, where visibility is a major source of variance in the incident radiance, our approach can reduce variance by more than an order of magnitude. Even in such complex scenes we can obtain accurate and low noise previews with full global illumination in a couple of seconds on a single mid-range CPU.
dcterms:title
Importance Caching for Complex Illumination Importance Caching for Complex Illumination
skos:prefLabel
Importance Caching for Complex Illumination Importance Caching for Complex Illumination
skos:notation
RIV/00216208:11320/12:10127580!RIV13-MSM-11320___
n4:predkladatel
n11:orjk%3A11320
n3:aktivita
n17:I
n3:aktivity
I
n3:cisloPeriodika
2
n3:dodaniDat
n13:2013
n3:domaciTvurceVysledku
n14:6335462
n3:druhVysledku
n19:J
n3:duvernostUdaju
n20:S
n3:entitaPredkladatele
n16:predkladatel
n3:idSjednocenehoVysledku
140866
n3:idVysledku
RIV/00216208:11320/12:10127580
n3:jazykVysledku
n10:eng
n3:klicovaSlova
Computer Graphics, Three-Dimensional Graphics and Realism-Raytracing, Radiosity
n3:klicoveSlovo
n7:Radiosity n7:Computer%20Graphics n7:Three-Dimensional%20Graphics%20and%20Realism-Raytracing
n3:kodStatuVydavatele
GB - Spojené království Velké Británie a Severního Irska
n3:kontrolniKodProRIV
[CEDB8E2284F3]
n3:nazevZdroje
Computer Graphics Forum
n3:obor
n5:IN
n3:pocetDomacichTvurcuVysledku
1
n3:pocetTvurcuVysledku
4
n3:rokUplatneniVysledku
n13:2012
n3:svazekPeriodika
31
n3:tvurceVysledku
Křivánek, Jaroslav Popov, Stefan Georgiev, Iliyan Slusallek, Philipp
n3:wos
000306181700019
s:issn
0167-7055
s:numberOfPages
10
n6:doi
10.1111/j.1467-8659.2012.03049.x
n18:organizacniJednotka
11320