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Minimal BRDF sampling for two-shot near-field reflectance acquisition

Authors:

Jannik Boll Nielsen,

Henrik Wann Jensen,

Ravi RamamoorthiAuthors Info & Claims

ACM Transactions on Graphics (TOG), Volume 35, Issue 6

Article No.: 188, Pages 1 - 12

https://doi.org/10.1145/2980179.2982396

Published: 05 December 2016 Publication History

Abstract

We develop a method to acquire the BRDF of a homogeneous flat sample from only two images, taken by a near-field perspective camera, and lit by a directional light source. Our method uses the MERL BRDF database to determine the optimal set of lightview pairs for data-driven reflectance acquisition. We develop a mathematical framework to estimate error from a given set of measurements, including the use of multiple measurements in an image simultaneously, as needed for acquisition from near-field setups. The novel error metric is essential in the near-field case, where we show that using the condition-number alone performs poorly. We demonstrate practical near-field acquisition of BRDFs from only one or two input images. Our framework generalizes to configurations like a fixed camera setup, where we also develop a simple extension to spatially-varying BRDFs by clustering the materials.

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Cited By

Miandji ETongbuasirilai THajisharif SKavoosighafi BUnger J(2024)FROST-BRDF: A Fast and Robust Optimal Sampling Technique for BRDF AcquisitionIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2024.335520030:7(4390-4402)Online publication date: Jul-2024
https://doi.org/10.1109/TVCG.2024.3355200
Li ZShen XZhou XHu YLi B(2024)Hyper-SNBRDF: Hypernetwork for Neural BRDF Using Sinusoidal Activation2024 International Conference on 3D Vision (3DV)10.1109/3DV62453.2024.00068(965-974)Online publication date: 18-Mar-2024
https://doi.org/10.1109/3DV62453.2024.00068
Ma XXu XZhang LZhou KWu H(2023)OpenSVBRDF: A Database of Measured Spatially-Varying ReflectanceACM Transactions on Graphics10.1145/361835842:6(1-14)Online publication date: 5-Dec-2023
https://dl.acm.org/doi/10.1145/3618358
Show More Cited By

Index Terms

Minimal BRDF sampling for two-shot near-field reflectance acquisition
1. Computing methodologies
  1. Computer graphics
    1. Rendering
      1. Reflectance modeling

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Published In

cover image ACM Transactions on Graphics

ACM Transactions on Graphics Volume 35, Issue 6

November 2016

1045 pages

ISSN:0730-0301

EISSN:1557-7368

DOI:10.1145/2980179

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Copyright © 2016 ACM.

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Publication History

Published: 05 December 2016

Published in TOG Volume 35, Issue 6

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Cited By

Miandji ETongbuasirilai THajisharif SKavoosighafi BUnger J(2024)FROST-BRDF: A Fast and Robust Optimal Sampling Technique for BRDF AcquisitionIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2024.335520030:7(4390-4402)Online publication date: Jul-2024
https://doi.org/10.1109/TVCG.2024.3355200
Li ZShen XZhou XHu YLi B(2024)Hyper-SNBRDF: Hypernetwork for Neural BRDF Using Sinusoidal Activation2024 International Conference on 3D Vision (3DV)10.1109/3DV62453.2024.00068(965-974)Online publication date: 18-Mar-2024
https://doi.org/10.1109/3DV62453.2024.00068
Ma XXu XZhang LZhou KWu H(2023)OpenSVBRDF: A Database of Measured Spatially-Varying ReflectanceACM Transactions on Graphics10.1145/361835842:6(1-14)Online publication date: 5-Dec-2023
https://dl.acm.org/doi/10.1145/3618358
Li BShi LMatusik W(2023)End-to-end Procedural Material Capture with Proxy-Free Mixed-Integer OptimizationACM Transactions on Graphics10.1145/359213242:4(1-15)Online publication date: 26-Jul-2023
https://dl.acm.org/doi/10.1145/3592132
Zhu PLai SChen MGuo JLiu YGuo Y(2023)SVBRDF Reconstruction by Transferring Lighting KnowledgeComputer Graphics Forum10.1111/cgf.1497342:7Online publication date: 5-Nov-2023
https://doi.org/10.1111/cgf.14973
Kang KGu MXie CYang XWu HZhou K(2023)Neural Reflectance Capture in the View-Illumination DomainIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2021.311737029:2(1450-1462)Online publication date: 1-Feb-2023
https://doi.org/10.1109/TVCG.2021.3117370
Schmitt CAntić BNeculai ALee JGeiger A(2023)Towards Scalable Multi-View Reconstruction of Geometry and MaterialsIEEE Transactions on Pattern Analysis and Machine Intelligence10.1109/TPAMI.2023.331434845:12(15850-15869)Online publication date: Dec-2023
https://doi.org/10.1109/TPAMI.2023.3314348
Sun CCai GLi ZYan KZhang CMarshall CHuang JZhao SDong Z(2023)Neural-PBIR Reconstruction of Shape, Material, and Illumination2023 IEEE/CVF International Conference on Computer Vision (ICCV)10.1109/ICCV51070.2023.01654(18000-18010)Online publication date: 1-Oct-2023
https://doi.org/10.1109/ICCV51070.2023.01654
Shi ZLin XSong Y(2023)An attention-embedded GAN for SVBRDF recovery from a single imageComputational Visual Media10.1007/s41095-022-0289-19:3(551-561)Online publication date: 22-Mar-2023
https://doi.org/10.1007/s41095-022-0289-1
Han HAlexoudi TVagionas CPleros NHardavellas N(2022)A Practical Shared Optical Cache With Hybrid MWSR/R-SWMR NoC for Multicore ProcessorsACM Journal on Emerging Technologies in Computing Systems10.1145/353101218:4(1-28)Online publication date: 13-Oct-2022
https://dl.acm.org/doi/10.1145/3531012
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