Lightcuts: a scalable approach to illumination
Bruce Walter, Sebastian Fernandez, Adam Arbree, Kavita Bala, Mike Donikian, Don Greenberg
Proceedings of SIGGRAPH 2005 (SIGGRAPH 2005)
Presentation: ppt, pdf
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.