Information
- Publication Type: Technical Report
- Workgroup(s)/Project(s): not specified
- Date: April 1996
- Number: TR-186-2-96-14
- Keywords: radiosity, stochastic, Monte Carlo, hierarchical, Galerkin, density estimation
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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BibTeX
@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.",
month = apr,
number = "TR-186-2-96-14",
address = "Favoritenstrasse 9-11/E193-02, A-1040 Vienna, Austria",
institution = "Institute of Computer Graphics and Algorithms, Vienna
University of Technology ",
note = "human contact: technical-report@cg.tuwien.ac.at",
keywords = "radiosity, stochastic, Monte Carlo, hierarchical, Galerkin,
density estimation",
URL = "https://www.cg.tuwien.ac.at/research/publications/1996/Tobler-1996-HSA/",
}