• 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