Estimating Homogeneous Data-driven BRDF Parameters from a Reflectance Map under Known Natural Lighting

Cooper, Victoria L.; Bieron, James C.; Peers, Pieter

Estimating Homogeneous Data-driven BRDF Parameters from a Reflectance Map under Known Natural Lighting

Files

023-026.pdf (883.95 KB)

Date

2019

Authors

Cooper, Victoria L.
Bieron, James C.
Peers, Pieter

Publisher

The Eurographics Association

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.

        @inproceedings{10.2312:mam.20191308
,
booktitle = {Workshop on Material Appearance Modeling
},
editor = {Klein, Reinhard and Rushmeier, Holly
},
title = {{Estimating Homogeneous Data-driven BRDF Parameters from a Reflectance Map under Known Natural Lighting
}},
author = {Cooper, Victoria L. and 
Bieron, James C. and 
Peers, Pieter
},
year = {2019
},
publisher = {The Eurographics Association
},
ISSN = {2309-5059
},
ISBN = {978-3-03868-080-2
},
DOI = {10.2312/mam.20191308
}
}