"An Adaptive Metric for BRDF Appearance Matching"
James C. Bieron, and Pieter Peers

Eurographics Workshop on Material Appearance Modeling, June 2020
Abstract
Image-based BRDF matching is a special case of inverse rendering, where the parameters of a BRDF model are optimized based on a photograph of a homogeneous material under natural lighting. Using a perceptual image metric, directly optimizing the difference between a rendering and a reference image can provide a close visual match between the model and reference material. However, perceptual image metrics rely on image-features and thus require full resolution renderings that can be costly to produce especially when embedded in an non-linear search procedure for the optimal BRDF parameters. Using a pixel-based metric, such as the square difference, can approximate the image error from a small subset of pixel. Unfortunately, pixel-based metrics are often a poor approximation of human perception of the material’s appearance. We show that comparable quality results to a perceptual metric can be obtained using an adaptive pixel-based metric that is optimized based on the appearance similarity of the material. As the core of our adaptive metric is pixel-based, our method is amendable to image-subsampling, thereby greatly reducing the computational cost.


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Related Publications
  • James C. Bieron, and Pieter Peers, "An Adaptive BRDF Fitting Metric", Computer Graphics Forum, Volume 39, Issue 4, July 2020,
Bibtex
@conference{Bieron:2020:AMB,
author = {Bieron, James C. and Peers, Pieter},
title = {An Adaptive Metric for BRDF Appearance Matching},
month = {June},
year = {2020},
booktitle = {Eurographics Workshop on Material Appearance Modeling},
}
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