"Estimating Homogeneous Data-Driven BRDF Parameters from a Reflectance Map under Known Natural Lighting"
Victoria L. Cooper, James C. Bieron, and Pieter Peers

Eurographics Workshop on Material Appearance Modeling, June 2019
Abstract
In this paper we demonstrate robust estimation of the model parameters of a fully-linear data-driven BRDF model from a reflectance map under known natural lighting. To regularize the estimation of the model parameters, we leverage the reflectance similarities within a material class. We approximate the space of homogeneous BRDFs using a Gaussian mixture model, and assign a material class to each Gaussian in the mixture model. Next, we compute a linear solution per material class. Finally, we select the best candidate as the final estimate. We demonstrate the efficacy and robustness of our method using the MERL BRDF database under a variety of natural lighting conditions.


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Related Publications
  • Victoria L. Cooper, James C. Bieron, and Pieter Peers, "Estimating Homogeneous Data-Driven BRDF Parameters from a Reflectance Map under Known Natural Lighting", CoRR, abs/1906.04777, June 2019,
Bibtex
@conference{Cooper:2019:EHD,
author = {Cooper, Victoria L. and Bieron, James C. and Peers, Pieter},
title = {Estimating Homogeneous Data-Driven {BRDF} Parameters from a Reflectance Map under Known Natural Lighting},
month = {June},
year = {2019},
booktitle = {Eurographics Workshop on Material Appearance Modeling},
doi = {http://doi.org/10.2312/mam.20191308},
}
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