Name
Abstract | ||
|---|---|---|
We present the Optimizing Control Variate (OCV) estimator a new estimator for Monte Carlo rendering. Based upon a deterministic sampling framework, OCV allows multiple importance sampling functions to be combined in one algorithm. Its optimizing nature addresses a major problem with control variate estimators for rendering: users supply a generic correlated function which is optimized for each estimate, rather than a single highly tuned one that must work well everywhere. We demonstrate OCV with both direct lighting and irradiance-caching examples, showing improvements in image error of over 35% in some cases, for little extra computation time. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1111/j.1467-8659.2006.00954.x | COMPUTER GRAPHICS FORUM |
Keywords | Field | DocType |
direct lighting, deterministic mixture sampling, control variates | Mathematical optimization,Importance sampling,Computer science,Control variates,Sampling (statistics),Rendering (computer graphics),Monte carlo rendering,Computation,Estimator | Journal |
Volume | Issue | ISSN |
25 | 3 | 0167-7055 |
Citations | PageRank | References |
5 | 0.76 | 7 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| ShaoHua Fan | 1 | 84 | 7.48 |
| Stephen Chenney | 2 | 438 | 36.67 |
| Bo Hu | 3 | 8 | 1.17 |
| Kam-Wah Tsui | 4 | 12 | 3.37 |
| Yu-Chi Lai | 5 | 117 | 17.42 |