Efficient BRDF Sampling Using Projected Deviation Vector Parameterization

Tanaboon Tongbuasirilai, Jonas Unger, Murat Kurt; The IEEE International Conference on Computer Vision (ICCV), 2017, pp. 153-158

Abstract


This paper presents a novel approach for efficient sampling of isotropic Bidirectional Reflectance Distribution Functions (BRDFs). Our approach builds upon a new parameterization, the Projected Deviation Vector parameterization, in which isotropic BRDFs can be described by two 1D functions. We show that BRDFs can be efficiently and accurately measured in this space using simple mechanical measurement setups. To demonstrate the utility of our approach, we perform a thorough numerical evaluation and show that the BRDFs reconstructed from measurements along the two 1D bases produce rendering results that are visually comparable to the reference BRDF measurements which are densely sampled over the 4D domain described by the standard hemispherical parameterization.

Related Material


[pdf]
[bibtex]
@InProceedings{Tongbuasirilai_2017_ICCV,
author = {Tongbuasirilai, Tanaboon and Unger, Jonas and Kurt, Murat},
title = {Efficient BRDF Sampling Using Projected Deviation Vector Parameterization},
booktitle = {The IEEE International Conference on Computer Vision (ICCV) Workshops},
month = {Oct},
year = {2017}
}