Abstract
As opposed to Monte Carlo integration the quasi-Monte Carlo method does not allow for an error estimate from the samples used for the integral approximation and the deterministic error bound is not accessible in the setting of computer graphics, since usually the integrands are of unbounded variation. We investigate the application of randomized quasi-Monte Carlo integration to bidirectional path tracing yielding much more efficient algorithms that exploit low-discrepancy sampling and at the same time allow for variance estimation.
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Kollig, T., Keller, A. (2002). Efficient Bidirectional Path Tracing by Randomized Quasi-Monte Carlo Integration. In: Fang, KT., Niederreiter, H., Hickernell, F.J. (eds) Monte Carlo and Quasi-Monte Carlo Methods 2000. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-56046-0_19
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DOI: https://doi.org/10.1007/978-3-642-56046-0_19
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