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Clustering for glossy global illumination

Editor: James D. Foley Authors:

Per H. Christensen,

Dani Lischinski,

Eric J. Stollnitz,

David H. SalesinAuthors Info & Claims

ACM Transactions on Graphics (TOG), Volume 16, Issue 1

Pages 3 - 33

https://doi.org/10.1145/237748.237749

Published: 01 January 1997 Publication History

Abstract

We present a new clustering algorithm for global illumination in complex environments. The new algorithm extends provious work on clustering for radiosity to allow for nondiffuse (glossy) reflectors. We represent clusters as points with directional distributions of outgoing and incoming radiance and importance, and we derive an error bound for transfers between these clusters. The algorithm groups input surfaces into a hierarchy of clusters, and then permits clusters to interact only if the error bound is below an acceptable tolerance. We show that the algorithm is asymptotically more efficient than previous clustering algorithms even when restricted to ideally diffuse environments. Finally, we demonstrate the performance of our method on two complex glossy environments.

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Index Terms

Clustering for glossy global illumination
1. Computing methodologies
  1. Computer graphics
    1. Image manipulation
      1. Texturing

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Information

Published In

cover image ACM Transactions on Graphics

ACM Transactions on Graphics Volume 16, Issue 1

Jan. 1997

104 pages

ISSN:0730-0301

EISSN:1557-7368

DOI:10.1145/237748

Editor:
James D. Foley
Georgia Institute of Technology, Atlanta

Issue’s Table of Contents

Copyright © 1997 ACM.

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 January 1997

Published in TOG Volume 16, Issue 1

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Xia SLu YLiu ZGuo JZhang J(2024)A Coupled Numerical Scheme for Simulating Liquid Metal Cooling Process in the Production of SuperalloysInternational Journal of Metalcasting10.1007/s40962-024-01312-w19:1(496-510)Online publication date: 22-Apr-2024
https://doi.org/10.1007/s40962-024-01312-w
Bohec MLemonnier DSaury D(2022)Model reduction of radiative heat transfer by a hierarchical radiosity methodNumerical Heat Transfer, Part A: Applications10.1080/10407782.2022.210239783:11(1175-1194)Online publication date: 27-Jul-2022
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Zhang GKong F(2019)Depth Learning Method of Many Light Rendering based on Matrix Row and Column Sampling2019 6th International Conference on Systems and Informatics (ICSAI)10.1109/ICSAI48974.2019.9010518(849-854)Online publication date: Nov-2019
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Lessig CDesbrun MFiume E(2014)A constructive theory of sampling for image synthesis using reproducing Kernel basesACM Transactions on Graphics10.1145/2601097.260114933:4(1-14)Online publication date: 27-Jul-2014
https://dl.acm.org/doi/10.1145/2601097.2601149
Sheng YShi YWang LNarasimhan S(2014)Translucent RadiosityIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2013.25620:7(1009-1021)Online publication date: 1-Jul-2014
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Tan ZWang DSrinivasan KPzekwas ASun R(2013)Numerical simulation of coupled radiation and convection from complex geometries7th AIAA/ASME Joint Thermophysics and Heat Transfer Conference10.2514/6.1998-2677Online publication date: 14-Feb-2013
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Sheng YShi YWang LNarasimhan SMeenakshisundaram GYoon SOlano MOtaduy M(2013)A practical analytic model for the radiosity of translucent scenesProceedings of the ACM SIGGRAPH Symposium on Interactive 3D Graphics and Games10.1145/2448196.2448206(63-70)Online publication date: 21-Mar-2013
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Leblanc LPoulin P(2013)Guaranteed Occlusion and Visibility in Cluster Hierarchical RadiosityRendering Techniques 200010.1007/978-3-7091-6303-0_9(89-100)Online publication date: 22-Jun-2013
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Willmott AHeckbert PGarland M(2011)Face Cluster RadiosityRendering Techniques’ 9910.1007/978-3-7091-6809-7_26(293-304)Online publication date: 20-Sep-2011
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