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We explore the notion of a Well-spaced Blue-noise Distribution (WBD) of points, which combines two desirable properties. First, the point distribution is random, as measured by its spectrum having blue noise. Second, it is well-spaced in the sense that the minimum separation distance between samples is large compared to the maximum coverage distance between(More)
We review our recent progress on efficient algorithms for generating well-spaced samples of high dimensional data, and for exploring and characterizing these data, the underlying domain, and functions over the domain. To our knowledge, these techniques have not yet been applied to computational topology, but the possible connections are worth considering.(More)
Blue noise refers to sample distributions that are random and well-spaced, with a variety of applications in graphics, geometry, and optimization. However, prior blue noise sampling algorithms typically suffer from the curse-of-dimensionality, especially when striving to cover a domain maximally. This hampers their applicability for high dimensional(More)
Figure 1: A sifted point cloud (right) retains much of the visual quality of the original (left), but using fewer points. 113k points were reduced by 16% in 19 seconds. Sifted disks are maximal and satisfy the same sizing function as the original. Abstract We introduce the Sifted Disk technique for locally resampling a point cloud in order to reduce the(More)
Poisson-disk sampling is similar to sphere packings: points have a minimum separation distance and the disks cover the domain. Disk centers are randomly placed. The method is popular in computer graphics because the random distribution avoids visual artifacts. This randomness can also be useful to avoid mesh-induced non-physical phenomena in simulations. We(More)
We introduce an algorithmic framework for tuning the spatial density of disks in a maximal random packing, without changing the sizing function or radii of disks. Starting from any maximal random packing such as a Maximal Poisson-disk Sampling (MPS), we iteratively relocate, inject (add), or eject (remove) disks, using a set of three successively(More)
Investigating algorithms and architectures to accelerate next-generation real-time computer graphics, with continued involvement in technology transfer to future NVIDIA products 2007–13 Graduate Student Researcher, Made fundamental contributions to techniques in the area of programmable graphics pipelines on modern GPUs, and proposed Piko, an abstraction to(More)
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