We present a fast, scalable algorithm to generate high-quality blue noise point distributions
of arbitrary density functions. At its core is a novel formulation of the recently-introduced …

Among the various approaches for producing point distributions with blue noise spectrum,
we argue for an optimization framework using Gaussian kernels. We show that with a wise …

In this article we survey techniques for the digital simulation of hand-made stippling—one of
the core techniques developed within non-photorealistic/expressive rendering. Over the …

In this paper, we survey recent approaches to blue-noise sampling and discuss their
beneficial applications. We discuss the sampling algorithms that use points as sampling …

This article presents a new method to optimally partition a geometric domain with capacity
constraints on the partitioned regions. It is an important problem in many fields, ranging from …

In this article we revisit the problem of blue noise sampling with a strong focus on the
spectral properties of the sampling patterns. Starting from the observation that oscillations in …

In this article, we study the generation of maximal Poisson-disk sets with varying radii. First,
we present a geometric analysis of gaps in such disk sets. This analysis is the basis for …

This paper presents a novel technique for resampling point clouds of a smooth surface. The
key contribution of this paper is the generalization of centroidal Voronoi tessellation (CVT) to …

Abstract Quasi‐Monte Carlo (QMC) methods exhibit a faster convergence rate than that of
classic Monte Carlo methods. This feature has made QMC prevalent in image synthesis …

We present a novel technique that produces two-dimensional low-discrepancy (LD) blue
noise point sets for sampling. Using one-dimensional binary van der Corput sequences, we …