Learn More
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)
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)
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)
Otitis media (OM) is the most common illness in children in the United States. Three-fourths of children under the age of three have OM at least once. Children with chronic OM, including OM with effusion and recurrent OM, will often have conductive hearing loss and communication difficulties, and need surgical treatment. Recent clinical studies provide(More)
  • 1