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Adaptive Direct Illumination Sampling

Publication at Faculty of Mathematics and Physics |
2016

Abstract

We present a new method for sampling direct illumination in scenes containing a large number of light sources. We divide a scene into cells and find a suitable clustering of the light sources for each of the cells.

The clusters are then importance sampled based on their estimated contribution. Our solution is unbiased, scales well with the number of light sources and can be easily incorporated into any existing path tracing rendering system.