“An error estimation framework for photon density estimation” by Hachisuka, Jarosz and Jensen

  • ©Toshiya Hachisuka, Wojciech Jarosz, and Henrik Wann Jensen

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Title:

    An error estimation framework for photon density estimation

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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.

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.
    2. Silverman, B. 1986. Density Estimation for Statistics and Data Analysis. Chapman and Hall, New York, NY.


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