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Abstract

Stochastic radiosity methods have become a standard tool for generating global illumination solutions for very large scenes. Unfortunately, these methods need scene descriptions that are premeshed to a very fine resolution, in order to compute an adequate solution of the global illumination. The algorithm proposed in this paper uses a stochastic Galerkin approach to incrementally calculate the illumination function. By tracking the illumination function at different levels of resolution it is possible to get a measure for the quality of the representation, and thus adaptively subdivide in places with inadequate accuracy. With this technique a hierarchical mesh is generated, that is based on the stochastic evaluation of global illumination.

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@techreport{Tobler-1996-HSA,
  title =      "A Hierarchical Subdivision Algorithm for Stochastic
                Radiosity Methods",
  author =     "Robert F. Tobler and Martin Feda and Werner Purgathofer and
               Alexander Wilkie",
  year =       "1996",
  abstract =   "Stochastic radiosity methods have become a standard tool for
               generating global illumination solutions for very large
               scenes. Unfortunately, these methods need scene descriptions
               that are premeshed to a very fine resolution, in order to
               compute an adequate solution of the global illumination. The
               algorithm proposed in this paper uses a stochastic Galerkin
               approach to incrementally calculate the illumination
               function. By tracking the illumination function at different
               levels of resolution it is possible to get a measure for the
               quality of the representation, and thus adaptively subdivide
               in places with inadequate accuracy. With this technique a
               hierarchical mesh is generated, that is based on the
               stochastic evaluation of                 global
               illumination.",
  address =    "Favoritenstrasse 9-11/186, A-1040 Vienna, Austria",
  institution = "Institute of Computer Graphics and Algorithms, Vienna
               University of Technology",
  note =       "human contact: technical-report@cg.tuwien.ac.at",
  month =      apr,
  number =     "TR-186-2-96-14",
  keywords =   "radiosity, stochastic, Monte Carlo, hierarchical, Galerkin,
               density estimation",
  URL =        "http://www.cg.tuwien.ac.at/research/publications/1996/Tobler-1996-HSA/",
}