Alexander Keller
Iliyan Georgiev
ABSTRACT
Light transport simulation is ruled by the radiance equation, which is an integral equation. Photorealistic image synthesis consists of computing functionals of the solution of the integral equation, which involves integration, too. However, in meaningful settings, none of the integrals can be computed analytically and, in fact, all these integrals need to be approximated using Monte Carlo and quasi-Monte Carlo methods. Generating uniformly distributed points in the unit-hypercube is at the core of all of these methods. The course teaches the algorithms behind and elaborates on the characteristics of different classes of uniformly distributed points to help selecting the points most efficient for a task.
Supplemental Material
- (APC<sup>+</sup>16) A. Ahmed, H. Perrier, D. Coeurjolly, V. Ostromoukhov, J. Guo, D. Yan, H. Huang, and O. Deussen. Low-discrepancy blue noise sampling. ACM Transactions on Graphics, 35(6):247:1--247:13, 2016. Google Scholar
Digital Library
- (CKK18) P Christensen, A. Kensler, and C. Kilpatrick. Progressive multi-jittered sample sequences. Computer Graphics Forum (Proceedings of the Eurographics Symposium on Rendering 2018), 37(4):21--33, 2018.Google ScholarCross Ref
- (GF16) I. Georgiev and M. Fajardo. Blue-noise dithered sampling. ACM SIGGRAPH 2016 Talks, 2016. Google ScholarDigital Library
- (Kel06) A. Keller. Myths of computer graphics. In H. Niederreiter, editor, Monte Carlo and Quasi-Monte Carlo Methods 2004, pages 217--243. Springer, 2006.Google ScholarCross Ref
- (Kel13) A. Keller. Quasi-Monte Carlo image synthesis in a nutshell. In J. Dick, F. Kuo, G. Peters, and I. Sloan, editors, Monte Carlo and Quasi-Monte Carlo Methods 2012, pages 203--238. Springer, 2013.Google Scholar
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