Name
Abstract | ||
|---|---|---|
Computing the light attenuation between two given points is an essential yet expensive task in volumetric light transport simulation. Existing unbiased transmittance estimators are all based on "null-scattering" random walks enabled by augmenting the media with fictitious matter. This formulation prevents the use of traditional Monte Carlo estimator variance analysis, thus the efficiency of such methods is understood from a mostly empirical perspective. In this paper, we present several novel integral formulations of volumetric transmittance in which existing estimators arise as direct Monte Carlo estimators. Breaking from physical intuition, we show that the null-scattering concept is not strictly required for unbiased transmittance estimation, but is a form of control variates for effectively reducing variance. Our formulations bring new insight into the problem and the efficiency of existing estimators. They also provide a framework for devising new types of transmittance estimators with distinct and complementary performance tradeoffs, as well as a clear recipe for applying sample stratification.
|
Year | DOI | Venue |
|---|---|---|
2019 | 10.1145/3355089.3356559 | ACM Transactions on Graphics (TOG) |
Keywords | Field | DocType |
Monte Carlo integration, null collision, null scattering, participating media, stochastic sampling, transmittance | Computer vision,Optics,Transmittance,Artificial intelligence,Mathematics | Journal |
Volume | Issue | ISSN |
38 | 6 | 0730-0301 |
Citations | PageRank | References |
1 | 0.38 | 0 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Iliyan Georgiev | 1 | 244 | 20.88 |
| Zackary Misso | 2 | 1 | 0.38 |
| Toshiya Hachisuka | 3 | 470 | 30.93 |
| Derek Nowrouzezahrai | 4 | 5 | 2.49 |
| Jaroslav Krivánek | 5 | 290 | 21.61 |
| Wojciech Jarosz | 6 | 1041 | 60.39 |