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Lightcuts: a scalable approach to illumination
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Source ACM Transactions on Graphics (TOG) archive
Volume 24 ,  Issue 3  (July 2005) table of contents
Proceedings of ACM SIGGRAPH 2005
SESSION: Appearance & illumination table of contents
Pages: 1098 - 1107  
Year of Publication: 2005
ISSN:0730-0301
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Authors
Bruce Walter  Program of Computer Graphics, Cornell University
Sebastian Fernandez  Program of Computer Graphics, Cornell University
Adam Arbree  Program of Computer Graphics, Cornell University
Kavita Bala  Program of Computer Graphics, Cornell University
Michael Donikian  Program of Computer Graphics, Cornell University
Donald P. Greenberg  Program of Computer Graphics, Cornell University
Publisher
ACM  New York, NY, USA
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ABSTRACT

Lightcuts is a scalable framework for computing realistic illumination. It handles arbitrary geometry, non-diffuse materials, and illumination from a wide variety of sources including point lights, area lights, HDR environment maps, sun/sky models, and indirect illumination. At its core is a new algorithm for accurately approximating illumination from many point lights with a strongly sublinear cost. We show how a group of lights can be cheaply approximated while bounding the maximum approximation error. A binary light tree and perceptual metric are then used to adaptively partition the lights into groups to control the error vs. cost tradeoff.We also introduce reconstruction cuts that exploit spatial coherence to accelerate the generation of anti-aliased images with complex illumination. Results are demonstrated for five complex scenes and show that lightcuts can accurately approximate hundreds of thousands of point lights using only a few hundred shadow rays. Reconstruction cuts can reduce the number of shadow rays to tens.


REFERENCES

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Collaborative Colleagues:
Bruce Walter: colleagues
Sebastian Fernandez: colleagues
Adam Arbree: colleagues
Kavita Bala: colleagues
Michael Donikian: colleagues
Donald P. Greenberg: colleagues