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Caltech Authors
Article . 1990
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Part of book or chapter of book . 1990
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Particle transport and image synthesis

Authors: Arvo, James; Kirk, David;

Particle transport and image synthesis

Abstract

The rendering equation is similar to the linear Boltzmann equation which has been widely studied in physics and nuclear engineering. Consequently, many of the powerful techniques which have been developed in these fields can be applied to problems in image synthesis. In this paper we adapt several statistical techniques commonly used in neutron transport to stochastic ray tracing and, more generally, to Monte Carlo solution of the rendering equation. First, we describe a technique known as Russian roulette which can be used to terminate the recursive tracing of rays without introducing statistical bias. We also examine the practice of creating ray trees in classical ray tracing in the light of a well-known technique in particle transport known as splitting . We show that neither ray trees nor paths as described in [10] constitute an optimal sampling plan in themselves and that a hybrid may be more efficient.

Country
United States
Related Organizations
Keywords

radiosity, ray tracing, Algorithms, Graphics, Boltzmann equation, Monte Carlo, particle transport, radiosity, ray tracing, rendering equation, 004, Boltzmann equation, rendering equation, particle transport, Graphics, Monte Carlo, Algorithms

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
96
Top 10%
Top 1%
Top 10%
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