Monte-Carlo Global Illumination Methods State of the Art and New Developments
László Szirmay‐Kalos · 2000
This paper presents the state of the art and recent developments of Monte-Carlo global illumination algorithms. First it surveys the basic tasks of global illumination, which can be formulated as the solution of either the rendering or the potential equation, then reviews the basic solution techniques, including inversion, expansion and iteration. The paper explains why stochastic approaches are good to solve these integral equations and highlights what kind of fundamental choices we have when designing such an algorithm. It compares, for example, finite-element and continuous methods, pure Monte-Carlo and quasi-Monte Carlo techniques, different versions of importance sampling, Russian roulette, etc. Then, a lot of methods are reviewed in a unified framework, that also allows to make comparisons. Keywords: Rendering and potential equations, Monte-Carlo and quasi-Monte Carlo quadratures, finite-element