A General BRDF Representation Based on Tensor Decomposition

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dc.contributor.authorBilgili, Ahmeten_US
dc.contributor.authorÖztürk, Aydnen_US
dc.contributor.authorKurt, Muraten_US
dc.contributor.editorEduard Groeller and Holly Rushmeieren_US
dc.date.accessioned2015-02-27T16:45:40Z
dc.date.available2015-02-27T16:45:40Z
dc.date.issued2011en_US
dc.description.abstractGenerating photo‐realistic images through Monte Carlo rendering requires efficient representation of light–surface interaction and techniques for importance sampling. Various models with good representation abilities have been developed but only a few of them have their importance sampling procedure. In this paper, we propose a method which provides a good bidirectional reflectance distribution function (BRDF) representation and efficient importance sampling procedure. Our method is based on representing BRDF as a function of tensor products. Four‐dimensional measured BRDF tensor data are factorized using Tucker decomposition. A large data set is used for comparing the proposed BRDF model with a number of well‐known BRDF models. It is shown that the underlying model provides good approximation to BRDFs.en_US
dc.description.number8
dc.description.seriesinformationComputer Graphics Forumen_US
dc.description.volume30
dc.identifier.doi10.1111/j.1467-8659.2011.02072.xen_US
dc.identifier.issn1467-8659en_US
dc.identifier.urihttps://doi.org/10.1111/j.1467-8659.2011.02072.xen_US
dc.publisherThe Eurographics Association and Blackwell Publishing Ltd.en_US
dc.titleA General BRDF Representation Based on Tensor Decompositionen_US
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