Robust Sample Budget Allocation for MIS

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dc.contributor.authorSzirmay-Kalos, Lászlóen_US
dc.contributor.authorSbert, Mateuen_US
dc.contributor.editorPelechano, Nuriaen_US
dc.contributor.editorVanderhaeghe, Daviden_US
dc.date.accessioned2022-04-22T08:16:10Z
dc.date.available2022-04-22T08:16:10Z
dc.date.issued2022
dc.description.abstractMultiple Importance Sampling (MIS) combines several sampling techniques. Its weighting scheme depends on how many samples are generated with each particular method. This paper examines the optimal determination of the number of samples allocated to each of the combined techniques taking into account that this decision can depend only on a relatively small number of previous samples. The proposed method is demonstrated with the combination of BRDF sampling and Light source sampling, and we show that due to its robustness, it can outperform the theoretically more accurate approaches.en_US
dc.description.sectionheadersRendering and Illumination
dc.description.seriesinformationEurographics 2022 - Short Papers
dc.identifier.doi10.2312/egs.20221022
dc.identifier.isbn978-3-03868-169-4
dc.identifier.issn1017-4656
dc.identifier.pages17-20
dc.identifier.pages4 pages
dc.identifier.urihttps://doi.org/10.2312/egs.20221022
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/egs20221022
dc.publisherThe Eurographics Associationen_US
dc.rightsAttribution 4.0 International License
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.titleRobust Sample Budget Allocation for MISen_US
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