Browsing by Author "Jarosz, Wojciech"

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    2017 Cover Image: Mixing Bowl
    (© 2017 The Eurographics Association and John Wiley & Sons Ltd., 2017) Marra, Alessia; Nitti, Maurizio; Papas, Marios; Müller, Thomas; Gross, Markus; Jarosz, Wojciech; ovák, Jan; Chen, Min and Zhang, Hao (Richard)
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    Analysis of Sample Correlations for Monte Carlo Rendering
    (The Eurographics Association and John Wiley & Sons Ltd., 2019) Singh, Gurprit; Öztireli, Cengiz; Ahmed, Abdalla G. M.; Coeurjolly, David; Subr, Kartic; Deussen, Oliver; Ostromoukhov, Victor; Ramamoorthi, Ravi; Jarosz, Wojciech; Giachetti, Andrea and Rushmeyer, Holly
    Modern physically based rendering techniques critically depend on approximating integrals of high dimensional functions representing radiant light energy. Monte Carlo based integrators are the choice for complex scenes and effects. These integrators work by sampling the integrand at sample point locations. The distribution of these sample points determines convergence rates and noise in the final renderings. The characteristics of such distributions can be uniquely represented in terms of correlations of sampling point locations. Hence, it is essential to study these correlations to understand and adapt sample distributions for low error in integral approximation. In this work, we aim at providing a comprehensive and accessible overview of the techniques developed over the last decades to analyze such correlations, relate them to error in integrators, and understand when and how to use existing sampling algorithms for effective rendering workflows.
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    Fourier Analysis of Correlated Monte Carlo Importance Sampling
    (© 2020 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd, 2020) Singh, Gurprit; Subr, Kartic; Coeurjolly, David; Ostromoukhov, Victor; Jarosz, Wojciech; Benes, Bedrich and Hauser, Helwig
    Fourier analysis is gaining popularity in image synthesis as a tool for the analysis of error in Monte Carlo (MC) integration. Still, existing tools are only able to analyse convergence under simplifying assumptions (such as randomized shifts) which are not applied in practice during rendering. We reformulate the expressions for bias and variance of sampling‐based integrators to unify non‐uniform sample distributions [importance sampling (IS)] as well as correlations between samples while respecting finite sampling domains. Our unified formulation hints at fundamental limitations of Fourier‐based tools in performing variance analysis for MC integration. At the same time, it reveals that, when combined with correlated sampling, IS can impact convergence rate by introducing or inhibiting discontinuities in the integrand. We demonstrate that the convergence of multiple importance sampling (MIS) is determined by the strategy which converges slowest and propose several simple approaches to overcome this limitation. We show that smoothing light boundaries (as commonly done in production to reduce variance) can improve (M)IS convergence (at a cost of introducing a small amount of bias) since it removes discontinuities within the integration domain. We also propose practical integrand‐ and sample‐mirroring approaches which cancel the impact of boundary discontinuities on the convergence rate of estimators.
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    Progressive Transient Photon Beams
    (© 2019 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd, 2019) Marco, Julio; Guillén, Ibón; Jarosz, Wojciech; Gutierrez, Diego; Jarabo, Adrian; Chen, Min and Benes, Bedrich
    In this work, we introduce a novel algorithm for transient rendering in participating media. Our method is consistent, robust and is able to generate animations of time‐resolved light transport featuring complex caustic light paths in media. We base our method on the observation that the spatial continuity provides an increased coverage of the temporal domain, and generalize photon beams to transient‐state. We extend stead‐state photon beam radiance estimates to include the temporal domain. Then, we develop a progressive variant of our approach which provably converges to the correct solution using finite memory by averaging independent realizations of the estimates with progressively reduced kernel bandwidths. We derive the optimal convergence rates accounting for space and time kernels, and demonstrate our method against previous consistent transient rendering methods for participating media.In this work, we introduce a novel algorithm for transient rendering in participating media. Our method is consistent, robust and is able to generate animations of time‐resolved light transport featuring complex caustic light paths in media. We base our method on the observation that the spatial continuity provides an increased coverage of the temporal domain, and generalize photon beams to transient‐state. We extend stead‐state photon beam radiance estimates to include the temporal domain. Then, we develop a progressive variant of our approach which provably converges to the correct solution using finite memory by averaging independent realizations of the estimates with progressively reduced kernel bandwidths. We derive the optimal convergence rates accounting for space and time kernels, and demonstrate our method against previous consistent transient rendering methods for participating media.