Importance Resampling for Global Illumination

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dc.contributor.authorTalbot, Justinen_US
dc.contributor.authorCline, Daviden_US
dc.contributor.authorEgbert, Parrisen_US
dc.contributor.editorKavita Bala and Philip Dutreen_US
dc.date.accessioned2014-01-27T14:48:35Z
dc.date.available2014-01-27T14:48:35Z
dc.date.issued2005en_US
dc.description.abstractThis paper develops importance resampling into a variance reduction technique for Monte Carlo integration. Importance resampling is a sample generation technique that can be used to generate more equally weighted samples for importance sampling. This can lead to significant variance reduction over standard importance sampling for common rendering problems. We show how to select the importance resampling parameters for near optimal variance reduction. We demonstrate the robustness of this technique on common global illumination problems and achieve a 10%-70% variance reduction over standard importance sampling for direct lighting. We conclude that further variance reduction could be achieved with cheaper sampling methods.en_US
dc.description.seriesinformationEurographics Symposium on Rendering (2005)en_US
dc.identifier.isbn3-905673-23-1en_US
dc.identifier.issn1727-3463en_US
dc.identifier.urihttps://doi.org/10.2312/EGWR/EGSR05/139-146en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectCategories and Subject Descriptors (according to ACM CCS): I.3.7 [Computer Graphics]: Three-dimensional Graphics and Realismen_US
dc.titleImportance Resampling for Global Illuminationen_US
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EGSR05: 16th Eurographics Symposium on Rendering