Two-Level Adaptive Sampling for Illumination Integrals using Bayesian Monte Carlo

dc.contributor.authorMarques, Ricardoen_US
dc.contributor.authorBouville, Christianen_US
dc.contributor.authorSantos, Luis P.en_US
dc.contributor.authorBouatouch, Kadien_US
dc.contributor.editorT. Bashford-Rogers and L. P. Santosen_US
dc.date.accessioned2016-04-26T07:56:14Z
dc.date.available2016-04-26T07:56:14Z
dc.date.issued2016en_US
dc.description.abstractBayesian Monte Carlo (BMC) is a promising integration technique which considerably broadens the theoretical tools that can be used to maximize and exploit the information produced by sampling, while keeping the fundamental property of data dimension independence of classical Monte Carlo (CMC). Moreover, BMC uses information that is ignored in the CMC method, such as the position of the samples and prior stochastic information about the integrand, which often leads to better integral estimates. Nevertheless, the use of BMC in computer graphics is still in an incipient phase and its application to more evolved and widely used rendering algorithms remains cumbersome. In this article we propose to apply BMC to a two-level adaptive sampling scheme for illumination integrals. We propose an efficient solution for the second level quadrature computation and show that the proposed method outperforms adaptive quasi-Monte Carlo in terms of image error and high frequency noise.en_US
dc.description.sectionheadersRenderingen_US
dc.description.seriesinformationEG 2016 - Short Papersen_US
dc.identifier.doi10.2312/egsh.20161016en_US
dc.identifier.issn1017-4656en_US
dc.identifier.pages65-68en_US
dc.identifier.urihttps://doi.org/10.2312/egsh.20161016en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectI.3.7 [Computer Graphics]en_US
dc.subjectThree Dimensional Graphics and Realismen_US
dc.subjectRaytracingen_US
dc.titleTwo-Level Adaptive Sampling for Illumination Integrals using Bayesian Monte Carloen_US
Files
Original bundle
Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
065-068.pdf
Size:
1.31 MB
Format:
Adobe Portable Document Format
Description: