DocumentCode
1362348
Title
Representativity for Robust and Adaptive Multiple Importance Sampling
Author
Pajot, Anthony ; Barthe, Loïc ; Paulin, Mathias ; Poulin, Pierre
Author_Institution
IRIT, Univ. Paul Sabatier, Toulouse, France
Volume
17
Issue
8
fYear
2011
Firstpage
1108
Lastpage
1121
Abstract
We present a general method enhancing the robustness of estimators based on multiple importance sampling (MIS) in a numerical integration context. MIS minimizes variance of estimators for a given sampling configuration, but when this configuration is less adapted to the integrand, the resulting estimator suffers from extra variance. We address this issue by introducing the notion of "representativity” of a sampling strategy, and demonstrate how it can be used to increase robustness of estimators, by adapting them to the integrand. We first show how to compute representativities using common rendering informations such as BSDF, photon maps, or caches in order to choose the best sampling strategy for MIS. We then give hints to generalize our method to any integration problem and demonstrate that it can be used successfully to enhance robustness in different common rendering algorithms.
Keywords
numerical analysis; rendering (computer graphics); MIS; adaptive multiple importance sampling; integration problem; numerical integration context; rendering informations; Estimation; Light sources; Lighting; Monte Carlo methods; Photonics; Rendering (computer graphics); Robustness; Monte-Carlo; three-dimensional graphics and realism.;
fLanguage
English
Journal_Title
Visualization and Computer Graphics, IEEE Transactions on
Publisher
ieee
ISSN
1077-2626
Type
jour
DOI
10.1109/TVCG.2010.230
Filename
5611512
Link To Document