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An error estimation framework for photon density estimation

Published:26 July 2010Publication History

ABSTRACT

Estimating error is an important task in rendering. For many predictive rendering applications such as simulation of car headlights, lighting design, or architectural design it is import to provide an estimate of the actual error to ensure confidence and accuracy of the results. Even for applications where accuracy is not critical, error estimation is still useful for improving aspects of the rendering algorithm. Examples include terminating the rendering algorithm automatically, adaptive sampling where the parameters of the rendering algorithm are adjusted dynamically to minimize the error, and interpolating sparsely sampled radiance within a given error bound.

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References

  1. Hachisuka, T., Ogaki, S., and Jensen, H. W. 2008. Progressive photon mapping. ACM Transactions on Graphics (Proceedings of SIGGRAPH Asia 2008) 27, 5, Article 130. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Silverman, B. 1986. Density Estimation for Statistics and Data Analysis. Chapman and Hall, New York, NY.Google ScholarGoogle Scholar

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  1. An error estimation framework for photon density estimation

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      • Published in

        cover image ACM Conferences
        SIGGRAPH '10: ACM SIGGRAPH 2010 Talks
        July 2010
        56 pages
        ISBN:9781450303941
        DOI:10.1145/1837026

        Copyright © 2010 Copyright is held by the author/owner(s).

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        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 26 July 2010

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