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Optimizing Control Variate Estimators for Rendering

Shaohua Fan, Stephen Chenney, Bo Hu, Kam-Wah Tsui, Yu-Chi Lai
Proceedings of Eurographics 2006 — sep 2006
Download the publication : OCV.pdf [739Ko]  
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.

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BibTex references

  author       = "Fan, Shaohua and Chenney, Stephen and Hu, Bo and Tsui, Kam-Wah and Lai, Yu-Chi",
  title        = "Optimizing Control Variate Estimators for Rendering",
  booktitle    = "Proceedings of Eurographics 2006",
  month        = "sep",
  year         = "2006",
  publisher    = "Eurographics Association",
  projecturl   = "http://pages.cs.wisc.edu/~shaohua/research/OCV/OCVRendering.html",
  url          = "http://graphics.cs.wisc.edu/Papers/2006/FCHTL06"

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