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Efficiently computing light transport in participating media in a manner that is robust to variations in media density, scattering albedo, and anisotropy is a difficult and important problem in realistic image synthesis. While many specialized rendering techniques can efficiently resolve subsets of transport in specific media, no single approach can(More)
Monte Carlo techniques for light transport simulation rely on importance sampling when constructing light transport paths. Previous work has shown that suitable sampling distributions can be recovered from particles distributed in the scene prior to rendering. We propose to represent the distributions by a parametric mixture model trained in an on-line(More)
Efficiently simulating light transport in various scenes with a single algorithm is a difficult and important problem in computer graphics. Two major issues have been shown to hinder the efficiency of the existing solutions: light transport due to multiple highly glossy or specular interactions, and scenes with complex visibility between the camera and(More)
The human visual system is sensitive to relative differences in luminance, but light transport simulation algorithms based on Metropolis sampling often result in a highly nonuniform relative error distribution over the rendered image. Although this issue has previously been addressed in the context of the Metropolis light transport algorithm, our work(More)
  • MASTER THESIS, Martin Šik, Generováńı vlas̊u interpolaćı
  • 2012
I would hereby like to thank my supervisor Jaroslav Křivánek for his supervision and counseling which guided me throughout my work. I would also like to express my thanks to all members of the Stubble software project which includes the hair interpolation described by my diploma thesis. I declare that I carried out this master thesis independently, and only(More)
Markov Chain Monte Carlo (MCMC) has recently received a lot of attention in light transport simulation research [Hanika et al. 2015; Hachisuka et al. 2014]. While these methods aim at high quality sampling of local extremes of the path space (so called <i>local exploration</i>), the other issue - discovering these extremes - has been so far neglected. Poor(More)
Figure 1: Our fast mesh sampling algorithm can place up to 78 million random sample points per second on a triangle mesh. We can use the algorithm, for example, to interactively distribute hair roots on a surface (a) or for sampling illumination from a complex luminaire, such as a projected HDR image, where uniform sampling produces a noisy image (b).(More)
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