Optimal Combination of Techniques in Multiple Importance Sampling

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F14%3A00221463" target="_blank" >RIV/68407700:21230/14:00221463 - isvavai.cz</a>

Výsledek na webu

<a href="http://animation.szpt.edu.cn/vrcai/index.html" target="_blank" >http://animation.szpt.edu.cn/vrcai/index.html</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Optimal Combination of Techniques in Multiple Importance Sampling

Popis výsledku v původním jazyce

Multiple Importance Sampling (MIS) technique has been widely used in Computer Graphics in rendering algorithms. MIS is based on weighting several sampling techniques into a single estimator. When the combination weights are taken such that the sample contributions are balanced, i.e. they are the same for all techniques, it becomes balance heuristic. It has been used since its invention almost exclusively on equal sampling for all techniques. The question whether unequal sampling can give better variance, has raised till now little interest. Based on the properties of balance heuristic MIS as a weighted mixture of distributions, where weights are proportional to the number of samples, we obtain for this kind of integral an implicit closed formula for the sampling, where we get the minimum variance for MIS. We also take into account the cost of each sampling technique. Although this closed formula can not be written in an explicit way, we outline an iterative procedure to obtain the opti

Název v anglickém jazyce

Optimal Combination of Techniques in Multiple Importance Sampling

Popis výsledku anglicky

Multiple Importance Sampling (MIS) technique has been widely used in Computer Graphics in rendering algorithms. MIS is based on weighting several sampling techniques into a single estimator. When the combination weights are taken such that the sample contributions are balanced, i.e. they are the same for all techniques, it becomes balance heuristic. It has been used since its invention almost exclusively on equal sampling for all techniques. The question whether unequal sampling can give better variance, has raised till now little interest. Based on the properties of balance heuristic MIS as a weighted mixture of distributions, where weights are proportional to the number of samples, we obtain for this kind of integral an implicit closed formula for the sampling, where we get the minimum variance for MIS. We also take into account the cost of each sampling technique. Although this closed formula can not be written in an explicit way, we outline an iterative procedure to obtain the opti

Druh

D - Stať ve sborníku

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2014

Kód důvěrnosti údajů

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

Název statě ve sborníku

Proceedings of VRCAI 2014 conference

ISBN

978-1-4503-3254-5

ISSN

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e-ISSN

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Počet stran výsledku

10

Strana od-do

141-150

Název nakladatele

ACM SIGGRAPH

Místo vydání

New York

Místo konání akce

Shenzen

Datum konání akce

30. 11. 2014

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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