“Importance sampling of many lights with adaptive tree splitting”

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Entry Number: 33

Title:

    Importance sampling of many lights with adaptive tree splitting

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Abstract:


    We present a technique to importance sample large collections of lights. A bounding volume hierarchy over all lights is traversed at each shading point using a single random number in a way that importance samples their predicted contribution. We further improve the performance of the algorithm by forcing splitting until the importance of a cluster is sufficiently representative of its contents.

References:


    Peter Shirley, Changyaw Wang, and Kurt Zimmerman. 1996. Monte Carlo Techniques for Direct Lighting Calculations. ACM Trans. Graph. 15, 1 (Jan. 1996), 1–36. Google ScholarDigital Library
    Petr Vévoda and Jaroslav Křivánek. 2016. Adaptive Direct Illumination Sampling. In SIGGRAPH ASIA 2016 Posters (SA ’16). ACM, New York, NY, USA, Article 43, 2 pages. Google ScholarDigital Library
    Bruce Walter, Sebastian Fernandez, Adam Arbree, Kavita Bala, Michael Donikian, and Donald P. Greenberg. 2005. Lightcuts: A Scalable Approach to Illumination. ACM Trans. Graph. 24, 3 (July 2005), 1098–1107.

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