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dc.contributor.authorLawrence, Jasonen_US
dc.contributor.authorRusinkiewicz, Szymonen_US
dc.contributor.authorRamamoorthi, Ravien_US
dc.contributor.editorKavita Bala and Philip Dutreen_US
dc.date.accessioned2014-01-27T14:48:20Z
dc.date.available2014-01-27T14:48:20Z
dc.date.issued2005en_US
dc.identifier.isbn3-905673-23-1en_US
dc.identifier.issn1727-3463en_US
dc.identifier.urihttp://dx.doi.org/10.2312/EGWR/EGSR05/011-020en_US
dc.description.abstractAs image-based surface reflectance and illumination gain wider use in physically-based rendering systems, it is becoming more critical to provide representations that allow sampling light paths according to the distribution of energy in these high-dimensional measured functions. In this paper, we apply algorithms traditionally used for curve approximation to reduce the size of a multidimensional tabulated Cumulative Distribution Function (CDF) by one to three orders of magnitude without compromising its fidelity. These adaptive representations enable new algorithms for sampling environment maps according to the local orientation of the surface and for multiple importance sampling of image-based lighting and measured BRDFs.en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectCategories and Subject Descriptors (according to ACM CCS): I.3.7 [Computer Graphics]: Three-Dimensional Graphics and Realism I.3.6 [Computer Graphics]: Methodology and Techniquesen_US
dc.titleAdaptive Numerical Cumulative Distribution Functions for Efficient Importance Samplingen_US
dc.description.seriesinformationEurographics Symposium on Renderingen_US


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