Improving Hierarchical Monte Carlo Radiosity Algorithms

Pope Jackson, Chalmers Alan

Research output: Contribution to journalArticle (Academic Journal)peer-review

Abstract

Hierarchical subdivision techniques remove the need for a-priori meshing of surfaces when approximating global illumination. In addition they allow a progressive refinement of the solution. However, when subdivision is based upon Monte Carlo methods, due to the stochastic nature of such techniques, subdivision decisions cannot be made unless a sufficiently large number of samples have been considered. Shadow boundaries are one of the main features such subdivision algorithms are designed to detect, but mesh elements that are in shadow receive less light, and hence are slower to subdivide. In this paper we investigate methods for modifying the Monte Carlo hierarchical subdivision algorithm to improve the detection of shadow boundaries and caustics.
Translated title of the contributionImproving Hierarchical Monte Carlo Radiosity Algorithms
Original languageEnglish
Pages (from-to)244-251
JournalThe 8-th International Conference in Central Europe on Computer Graphics, Visualization and Interactive Digital Media 2000
Publication statusPublished - 2000

Bibliographical note

ISBN: 8070826126
Publisher: University of West Bohemia
Name and Venue of Conference: The 8-th International Conference in Central Europe on Computer Graphics, Visualization and Interactive Digital Media 2000
Other identifier: 1000440

Fingerprint

Dive into the research topics of 'Improving Hierarchical Monte Carlo Radiosity Algorithms'. Together they form a unique fingerprint.

Cite this