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    Optimal Deterministic Mixture Sampling

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    Date
    2019
    Author
    Sbert, Mateu
    Havran, Vlastimil ORCID
    Szirmay-Kalos, László
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    Abstract
    Multiple Importance Sampling (MIS) can combine several sampling techniques preserving their advantages. For example, we can consider different Monte Carlo rendering methods generating light path samples proportionally only to certain factors of the integrand. MIS then becomes equivalent to the application of the mixture of individual sampling densities, thus can simultaneously mimic the densities of all considered techniques. The weights of the mixture sampling depends on how many samples are generated with each particular method. This paper examines the optimal determination of this parameter. The proposed method is demonstrated with the combination of BRDF sampling and Light source sampling, and we show that it not only outperforms the application of the two individual methods, but is superior to other recent combination strategies and is close to the theoretical optimum.
    BibTeX
    @inproceedings {10.2312:egs.20191018,
    booktitle = {Eurographics 2019 - Short Papers},
    editor = {Cignoni, Paolo and Miguel, Eder},
    title = {{Optimal Deterministic Mixture Sampling}},
    author = {Sbert, Mateu and Havran, Vlastimil and Szirmay-Kalos, László},
    year = {2019},
    publisher = {The Eurographics Association},
    ISSN = {1017-4656},
    DOI = {10.2312/egs.20191018}
    }
    URI
    https://doi.org/10.2312/egs.20191018
    https://diglib.eg.org:443/handle/10.2312/egs20191018
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    Eurographics Association copyright © 2013 - 2023 
    Send Feedback | Contact - Imprint | Data Privacy Policy | Disable Google Analytics
    Theme by @mire NV
    System hosted at  Graz University of Technology.
    TUGFhA