Visibility-Aware Progressive Farthest Point Sampling on the GPU

dc.contributor.authorBrandt, Saschaen_US
dc.contributor.authorJähn, Claudiusen_US
dc.contributor.authorFischer, Matthiasen_US
dc.contributor.authorHeide, Friedhelm Meyer auf deren_US
dc.contributor.editorLee, Jehee and Theobalt, Christian and Wetzstein, Gordonen_US
dc.date.accessioned2019-10-14T05:08:27Z
dc.date.available2019-10-14T05:08:27Z
dc.date.issued2019
dc.description.abstractIn this paper, we present the first algorithm for progressive sampling of 3D surfaces with blue noise characteristics that runs entirely on the GPU. The performance of our algorithm is comparable to state-of-the-art GPU Poisson-disk sampling methods, while additionally producing ordered sequences of samples where every prefix exhibits good blue noise properties. The basic idea is, to reduce the 3D sampling domain to a set of 2.5D images which we sample in parallel utilizing the rasterization hardware of current GPUs. This allows for simple visibility-aware sampling that only captures the surface as seen from outside the sampled object, which is especially useful for point-based level-of-detail rendering methods. However, our method can be easily extended for sampling the entire surface without changing the basic algorithm. We provide a statistical analysis of our algorithm and show that it produces good blue noise characteristics for every prefix of the resulting sample sequence and analyze the performance of our method compared to related state-of-the-art sampling methods.en_US
dc.description.number7
dc.description.sectionheadersRendering and Sampling
dc.description.seriesinformationComputer Graphics Forum
dc.description.volume38
dc.identifier.doi10.1111/cgf.13848
dc.identifier.issn1467-8659
dc.identifier.pages413-424
dc.identifier.urihttps://doi.org/10.1111/cgf.13848
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1111/cgf13848
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.subjectComputing methodologies
dc.subjectRasterization
dc.subjectPoint
dc.subjectbased models
dc.subjectTheory of computation
dc.subjectComputational geometry
dc.titleVisibility-Aware Progressive Farthest Point Sampling on the GPUen_US
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