research-article

genBRDF: discovering new analytic BRDFs with genetic programming

Authors:

Jason Lawrence,

Westley WeimerAuthors Info & Claims

ACM Transactions on Graphics (TOG), Volume 33, Issue 4

Article No.: 114, Pages 1 - 11

https://doi.org/10.1145/2601097.2601193

Published: 27 July 2014 Publication History

Abstract

We present a framework for learning new analytic BRDF models through Genetic Programming that we call genBRDF. This approach to reflectance modeling can be seen as an extension of traditional methods that rely either on a phenomenological or empirical process. Our technique augments the human effort involved in deriving mathematical expressions that accurately characterize complex high-dimensional reflectance functions through a large-scale optimization. We present a number of analysis tools and data visualization techniques that are crucial to sifting through the large result sets produced by genBRDF in order to identify fruitful expressions. Additionally, we highlight several new models found by genBRDF that have not previously appeared in the BRDF literature. These new BRDF models are compact and more accurate than current state-of-the-art alternatives.

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Cited By

Tamisier ERibardière MMeneveaux DHorna SPoulin P(2024)A data-driven correction for the masking model of SmithJournal of the Optical Society of America A10.1364/JOSAA.530840Online publication date: 2-Aug-2024
https://doi.org/10.1364/JOSAA.530840
Atanasov AKoylazov VDimov RWilkie A(2022)Microsurface TransformationsComputer Graphics Forum10.1111/cgf.1459041:4(105-116)Online publication date: 30-Jul-2022
https://doi.org/10.1111/cgf.14590
Shi WDorsey JRushmeier H(2022)Learning-Based Inverse Bi-Scale Material Fitting From Tabular BRDFsIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2020.302602128:4(1810-1823)Online publication date: 1-Apr-2022
https://doi.org/10.1109/TVCG.2020.3026021
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Index Terms

genBRDF: discovering new analytic BRDFs with genetic programming
1. Computing methodologies
  1. Computer graphics
    1. Image manipulation
      1. Texturing

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Published In

cover image ACM Transactions on Graphics

ACM Transactions on Graphics Volume 33, Issue 4

July 2014

1366 pages

ISSN:0730-0301

EISSN:1557-7368

DOI:10.1145/2601097

Issue’s Table of Contents

Copyright © 2014 ACM.

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Publication History

Published: 27 July 2014

Published in TOG Volume 33, Issue 4

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Cited By

Tamisier ERibardière MMeneveaux DHorna SPoulin P(2024)A data-driven correction for the masking model of SmithJournal of the Optical Society of America A10.1364/JOSAA.530840Online publication date: 2-Aug-2024
https://doi.org/10.1364/JOSAA.530840
Atanasov AKoylazov VDimov RWilkie A(2022)Microsurface TransformationsComputer Graphics Forum10.1111/cgf.1459041:4(105-116)Online publication date: 30-Jul-2022
https://doi.org/10.1111/cgf.14590
Shi WDorsey JRushmeier H(2022)Learning-Based Inverse Bi-Scale Material Fitting From Tabular BRDFsIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2020.302602128:4(1810-1823)Online publication date: 1-Apr-2022
https://doi.org/10.1109/TVCG.2020.3026021
Zheng CZheng RWang RZhao SBao H(2021)A Compact Representation of Measured BRDFs Using Neural ProcessesACM Transactions on Graphics10.1145/349038541:2(1-15)Online publication date: 29-Nov-2021
https://dl.acm.org/doi/10.1145/3490385
Lavoué GBonneel NFarrugia JSoler C(2021)Perceptual quality of BRDF approximations: dataset and metricsComputer Graphics Forum10.1111/cgf.14263640:2(327-338)Online publication date: 4-Jun-2021
https://doi.org/10.1111/cgf.142636
Bernardi AGadia DMaggiorini DPalazzi CRipamonti L(2021)Procedural generation of materials for real-time renderingMultimedia Tools and Applications10.1007/s11042-020-09141-980:9(12969-12990)Online publication date: 1-Apr-2021
https://dl.acm.org/doi/10.1007/s11042-020-09141-9
Sole AGuarnera GFarup INussbaum P(2021)Measurement and rendering of complex non-diffuse and goniochromatic packaging materialsThe Visual Computer: International Journal of Computer Graphics10.1007/s00371-020-01980-937:8(2207-2220)Online publication date: 1-Aug-2021
https://dl.acm.org/doi/10.1007/s00371-020-01980-9
Kurt M(2021)GenSSS: a genetic algorithm for measured subsurface scattering representationThe Visual Computer: International Journal of Computer Graphics10.1007/s00371-020-01800-037:2(307-323)Online publication date: 1-Feb-2021
https://dl.acm.org/doi/10.1007/s00371-020-01800-0
Bieron JPeers P(2020)An Adaptive BRDF Fitting MetricComputer Graphics Forum10.1111/cgf.1405439:4(59-74)Online publication date: 20-Jul-2020
https://doi.org/10.1111/cgf.14054
Rainer GGhosh AJakob WWeyrich T(2020)Unified Neural Encoding of BTFsComputer Graphics Forum10.1111/cgf.1392139:2(167-178)Online publication date: 13-Jul-2020
https://doi.org/10.1111/cgf.13921
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