Improving the Dwivedi Sampling Scheme

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dc.contributor.authorMeng, Johannesen_US
dc.contributor.authorHanika, Johannesen_US
dc.contributor.authorDachsbacher, Carstenen_US
dc.contributor.editorElmar Eisemann and Eugene Fiumeen_US
dc.date.accessioned2016-06-17T14:09:26Z
dc.date.available2016-06-17T14:09:26Z
dc.date.issued2016en_US
dc.description.abstractDespite recent advances in Monte Carlo rendering techniques, dense, high-albedo participating media such as wax or skin still remain a difficult problem. In such media, random walks tend to become very long, but may still lead to a large contribution to the image. The Dwivedi sampling scheme, which is based on zero variance random walks, biases the sampling probability distributions to exit the medium as quickly as possible. This can reduce variance considerably under the assumption of a locally homogeneous medium with constant phase function. Prior work uses the normal at the Point of Entry as the bias direction. We demonstrate that this technique can fail in common scenarios such as thin geometry with a strong backlight. We propose two new biasing strategies, Closest Point and Incident Illumination biasing, and show that these techniques can speed up convergence by up to an order of magnitude. Additionally, we propose a heuristic approach for combining biased and classical sampling techniques using Multiple Importance Sampling.en_US
dc.description.number4en_US
dc.description.sectionheadersSamplingen_US
dc.description.seriesinformationComputer Graphics Forumen_US
dc.description.volume35en_US
dc.identifier.doi10.1111/cgf.12947en_US
dc.identifier.issn1467-8659en_US
dc.identifier.pages037-044en_US
dc.identifier.urihttps://doi.org/10.1111/cgf.12947en_US
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.subjectComputer Graphics [I.3.7]en_US
dc.subjectThree Dimensional Graphics and Realismen_US
dc.subjectRaytracingen_US
dc.titleImproving the Dwivedi Sampling Schemeen_US
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