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Numerical verification of bidirectional reflectance distribution functions for physical plausibility

Published: 07 October 2013 Publication History

Abstract

The implementations of a couple of often used Bidirectional Reflectance Distribution Functions (BRDFs) are numerically verified against the three conditions for physical plausibility. These conditions are positivity, symmetry (sometimes referred to as reciprocity) and conservation of energy. The focus of this paper is the numerical tests implemented to analyse and verify the BRDF implementations as physically plausible. A concise list of BRDF formulas, modified as required for physical plausibility, is however also presented which to the authors' best knowledge has not yet been presented in the literature.

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  1. Numerical verification of bidirectional reflectance distribution functions for physical plausibility

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    cover image ACM Other conferences
    SAICSIT '13: Proceedings of the South African Institute for Computer Scientists and Information Technologists Conference
    October 2013
    398 pages
    ISBN:9781450321129
    DOI:10.1145/2513456
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    • Amazon: Amazon.com
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    • IBM: IBM

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 07 October 2013

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    Author Tags

    1. BRDF
    2. model verification
    3. physically plausible

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    • Research-article

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    SAICSIT '13
    Sponsor:
    • Amazon
    • Rhodes Univ.
    • IBM

    Acceptance Rates

    SAICSIT '13 Paper Acceptance Rate 48 of 89 submissions, 54%;
    Overall Acceptance Rate 187 of 439 submissions, 43%

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    • (2024)Light curve attitude estimation using particle swarm optimizersAdvances in Space Research10.1016/j.asr.2024.09.00874:11(5619-5638)Online publication date: Dec-2024
    • (2023)A Reciprocal Heuristic Model for Diffuse Scattering From Walls and SurfacesIEEE Transactions on Antennas and Propagation10.1109/TAP.2023.327879671:7(6072-6083)Online publication date: Jul-2023
    • (2018)State-of-the-art review of solar design tools and methods for assessing daylighting and solar potential for building-integrated photovoltaicsRenewable and Sustainable Energy Reviews10.1016/j.rser.2017.05.08081(1296-1328)Online publication date: Jan-2018
    • (2017)A path reuse method for specular surface reflection in Monte Carlo path tracing2017 International Conference on Applied System Innovation (ICASI)10.1109/ICASI.2017.7988282(1759-1762)Online publication date: May-2017
    • (2017)Full BRDF Reconstruction Using CNNs from Partial Photometric Stereo-Light Field Data2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)10.1109/CVPRW.2017.219(1726-1734)Online publication date: Jul-2017
    • (2016)Polishing mechanism of light-initiated dental composite: Geometric optics approachJournal of the Formosan Medical Association10.1016/j.jfma.2015.10.010115:12(1053-1060)Online publication date: Dec-2016
    • (2014)Light Beam Tracing for Multi-Bounce Specular and Glossy Transport PathsProceedings of the Southern African Institute for Computer Scientist and Information Technologists Annual Conference 2014 on SAICSIT 2014 Empowered by Technology10.1145/2664591.2664610(199-208)Online publication date: 29-Sep-2014

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