Technical Papers

Sampling

Thursday, 25 July 9:00 AM - 10:30 AM
Session Chair: Philip Dutré, Katholieke Universiteit Leuven

Line-Segment Sampling With Blue-Noise Properties

This paper presents a frequency analysis of line-segment sampling. Based on the analysis, it proposes a line-segment sampling scheme to preserve blue-noise properties of samples that can significantly reduce noise and aliasing artifacts in reconstruction results.

Xin Sun
Microsoft Research Asia

Kun Zhou
Zhejiang University

Jie Guo
Nanjing University, Institute of Software, Chinese Academy of Sciences

Guofu Xie
Nanjing University

Jingui Pan
Nanjing University

Wencheng Wang
Nanjing University, Institute of Software, Chinese Academy of Sciences

Baining Guo
Microsoft Research Asia

Blue-Noise Sampling With Controlled Aliasing

Exploration of the relationship between the spatial and spectral properties of sampling patterns. The method not only synthesizes blue-noise patterns with a desired spectral response, but also gains control over the amount of aliasing that occurs in the sampled images.

Daniel Heck
Universität Konstanz

Thomas Schlömer
Universität Konstanz

Oliver Deussen
Universität Konstanz

Gap Processing for Adaptive Maximal Poisson-Disk Sampling

A study of the generation of maximal Poisson-disk sets with varying radii in Euclidean space and on manifolds. The work can be applied to generate high-quality triangle meshes.

Dong-Ming Yan
King Abdullah University of Science and Technology

Peter Wonka
King Abdullah University of Science and Technology

Fourier Analysis of Stochastic Sampling Strategies for Assessing Bias and Variance in Integration

This simple algorithm controllably trades off bias for variance in Monte Carlo integration. It is motivated using a Fourier-domain analysis of Monte Carlo integration with equations for bias and variance of the estimator in terms of the Fourier spectrum of the sampling pattern.

Kartic Subr
University College London

Jan Kautz
University College London