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Adaptive Matrix Completion for Fast Visibility Computations with Many Lights Rendering
Author(s) -
Wang S.,
Holzschuch N.
Publication year - 2020
Publication title -
computer graphics forum
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.578
H-Index - 120
eISSN - 1467-8659
pISSN - 0167-7055
DOI - 10.1111/cgf.14053
Subject(s) - global illumination , computer science , rendering (computer graphics) , visibility , computer graphics (images) , computer vision , bottleneck , radiance , artificial intelligence , computation , matrix completion , cluster analysis , algorithm , physics , quantum mechanics , optics , gaussian , embedded system
Several fast global illumination algorithms rely on the Virtual Point Lights framework. This framework separates illumination into two steps: first, propagate radiance in the scene and store it in virtual lights, then gather illumination from these virtual lights. To accelerate the second step, virtual lights and receiving points are grouped hierarchically, for example using Multi‐Dimensional Lightcuts. Computing visibility between clusters of virtual lights and receiving points is a bottleneck. Separately, matrix completion algorithms reconstruct completely a low‐rank matrix from an incomplete set of sampled elements. In this paper, we use adaptive matrix completion to approximate visibility information after an initial clustering step. We reconstruct visibility information using as little as 10 % to 20 % samples for most scenes, and combine it with shading information computed separately, in parallel on the GPU. Overall, our method computes global illumination 3 or more times faster than previous state‐of‐the‐art methods.