Browsing by Author "Meister, Daniel"

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    Neural Sequence Transformation
    (The Eurographics Association and John Wiley & Sons Ltd., 2021) Mukherjee, Sabyasachi; Mukherjee, Sayan; Hua, Binh-Son; Umetani, Nobuyuki; Meister, Daniel; Zhang, Fang-Lue and Eisemann, Elmar and Singh, Karan
    Monte Carlo integration is a technique for numerically estimating a definite integral by stochastically sampling its integrand. These samples can be averaged to make an improved estimate, and the progressive estimates form a sequence that converges to the integral value on the limit. Unfortunately, the sequence of Monte Carlo estimates converges at a rate of O(pn), where n denotes the sample count, effectively slowing down as more samples are drawn. To overcome this, we can apply sequence transformation, which transforms one converging sequence into another with the goal of accelerating the rate of convergence. However, analytically finding such a transformation for Monte Carlo estimates can be challenging, due to both the stochastic nature of the sequence, and the complexity of the integrand. In this paper, we propose to leverage neural networks to learn sequence transformations that improve the convergence of the progressive estimates of Monte Carlo integration. We demonstrate the effectiveness of our method on several canonical 1D integration problems as well as applications in light transport simulation.
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    Ray Classification for Accelerated BVH Traversal
    (The Eurographics Association and John Wiley & Sons Ltd., 2019) Hendrich, Jakub; Pospíšil, Adam; Meister, Daniel; Bittner, Jiří; Boubekeur, Tamy and Sen, Pradeep
    For ray tracing based methods, traversing a hierarchical acceleration data structure takes up a substantial portion of the total rendering time. We propose an additional data structure which cuts off large parts of the hierarchical traversal. We use the idea of ray classification combined with the hierarchical scene representation provided by a bounding volume hierarchy. We precompute short arrays of indices to subtrees inside the hierarchy and use them to initiate the traversal for a given ray class. This arrangement is compact enough to be cache-friendly, preventing the method from negating its traversal gains by excessive memory traffic. The method is easy to use with existing renderers which we demonstrate by integrating it to the PBRT renderer. The proposed technique reduces the number of traversal steps by 42% on average, saving around 15% of time of finding ray-scene intersection on average.
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    A Survey on Bounding Volume Hierarchies for Ray Tracing
    (The Eurographics Association and John Wiley & Sons Ltd., 2021) Meister, Daniel; Ogaki, Shinji; Benthin, Carsten; Doyle, Michael J.; Guthe, Michael; Bittner, Jirí; Bühler, Katja and Rushmeier, Holly
    Ray tracing is an inherent part of photorealistic image synthesis algorithms. The problem of ray tracing is to find the nearest intersection with a given ray and scene. Although this geometric operation is relatively simple, in practice, we have to evaluate billions of such operations as the scene consists of millions of primitives, and the image synthesis algorithms require a high number of samples to provide a plausible result. Thus, scene primitives are commonly arranged in spatial data structures to accelerate the search. In the last two decades, the bounding volume hierarchy (BVH) has become the de facto standard acceleration data structure for ray tracing-based rendering algorithms in offline and recently also in real-time applications. In this report, we review the basic principles of bounding volume hierarchies as well as advanced state of the art methods with a focus on the construction and traversal. Furthermore, we discuss industrial frameworks, specialized hardware architectures, other applications of bounding volume hierarchies, best practices, and related open problems.