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A Significance Cache for Accelerating Global Illumination
Author(s) -
BashfordRogers Thomas,
Debattista Kurt,
Chalmers Alan
Publication year - 2012
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/j.1467-8659.2012.02099.x
Subject(s) - global illumination , computer science , bidirectional reflectance distribution function , rendering (computer graphics) , importance sampling , monte carlo method , cache , sampling (signal processing) , sample (material) , variance (accounting) , computer vision , algorithm , artificial intelligence , computer graphics (images) , reflectivity , mathematics , parallel computing , statistics , optics , physics , chemistry , accounting , filter (signal processing) , chromatography , business
Rendering using physically based methods requires substantial computational resources. Most methods that are physically based use straightforward techniques that may excessively compute certain types of light transport, while ignoring more important ones. Importance sampling is an effective and commonly used technique to reduce variance in such methods. Most current approaches for physically based rendering based on Monte Carlo methods sample the BRDF and cosine term, but are unable to sample the indirect illumination as this is the term that is being computed. Knowledge of the incoming illumination can be especially useful in the case of hard to find light paths, such as caustics or scenes which rely primarily on indirect illumination. To facilitate the determination of such paths, we propose a caching scheme which stores important directions, and is analytically sampled to calculate important paths. Results show an improvement over BRDF sampling and similar illumination importance sampling.