Analysis of Sample Correlations for Monte Carlo Rendering

Simple item page
dc.contributor.authorSingh, Gurpriten_US
dc.contributor.authorĂ–ztireli, Cengizen_US
dc.contributor.authorAhmed, Abdalla G. M.en_US
dc.contributor.authorCoeurjolly, Daviden_US
dc.contributor.authorSubr, Karticen_US
dc.contributor.authorDeussen, Oliveren_US
dc.contributor.authorOstromoukhov, Victoren_US
dc.contributor.authorRamamoorthi, Ravien_US
dc.contributor.authorJarosz, Wojciechen_US
dc.contributor.editorGiachetti, Andrea and Rushmeyer, Hollyen_US
dc.date.accessioned2019-05-05T17:52:06Z
dc.date.available2019-05-05T17:52:06Z
dc.date.issued2019
dc.description.abstractModern physically based rendering techniques critically depend on approximating integrals of high dimensional functions representing radiant light energy. Monte Carlo based integrators are the choice for complex scenes and effects. These integrators work by sampling the integrand at sample point locations. The distribution of these sample points determines convergence rates and noise in the final renderings. The characteristics of such distributions can be uniquely represented in terms of correlations of sampling point locations. Hence, it is essential to study these correlations to understand and adapt sample distributions for low error in integral approximation. In this work, we aim at providing a comprehensive and accessible overview of the techniques developed over the last decades to analyze such correlations, relate them to error in integrators, and understand when and how to use existing sampling algorithms for effective rendering workflows.en_US
dc.description.documenttypestar
dc.description.number2
dc.description.sectionheadersState of the Art Reports
dc.description.seriesinformationComputer Graphics Forum
dc.description.volume38
dc.identifier.doi10.1111/cgf.13653
dc.identifier.issn1467-8659
dc.identifier.pages473-491
dc.identifier.urihttps://doi.org/10.1111/cgf.13653
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1111/cgf13653
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.subjectMathematics of computing
dc.subjectComputation of transforms
dc.subjectStochastic processes
dc.subjectNumber
dc.subjecttheoretic computations
dc.subjectComputing methodologies
dc.subjectRay tracing
dc.titleAnalysis of Sample Correlations for Monte Carlo Renderingen_US
Files
Collections
EG 2019 - STARs (CGF 38-2)