Stochastic sampling in computer graphics
ACM Transactions on Graphics (TOG)
Digital halftoning
Generating antialiased images at low sampling densities
SIGGRAPH '87 Proceedings of the 14th annual conference on Computer graphics and interactive techniques
SIGGRAPH '92 Proceedings of the 19th annual conference on Computer graphics and interactive techniques
Fast Fourier transforms for nonequispaced data
SIAM Journal on Scientific Computing
Antialiasing through stochastic sampling
SIGGRAPH '85 Proceedings of the 12th annual conference on Computer graphics and interactive techniques
Spectral compression of mesh geometry
Proceedings of the 27th annual conference on Computer graphics and interactive techniques
Digital and Analog Communication Systems
Digital and Analog Communication Systems
Principles of Digital Image Synthesis
Principles of Digital Image Synthesis
Digital Image Warping
Interactive geometry remeshing
Proceedings of the 29th annual conference on Computer graphics and interactive techniques
Advanced Global Illumination
Physically Based Rendering: From Theory to Implementation
Physically Based Rendering: From Theory to Implementation
Fast hierarchical importance sampling with blue noise properties
ACM SIGGRAPH 2004 Papers
Wavelet importance sampling: efficiently evaluating products of complex functions
ACM SIGGRAPH 2005 Papers
Recursive Wang tiles for real-time blue noise
ACM SIGGRAPH 2006 Papers
Interactive decal compositing with discrete exponential maps
ACM SIGGRAPH 2006 Papers
Rotational symmetry field design on surfaces
ACM SIGGRAPH 2007 papers
Design of tangent vector fields
ACM SIGGRAPH 2007 papers
ACM SIGGRAPH 2007 papers
Parallel Poisson disk sampling
ACM SIGGRAPH 2008 papers
Direct sampling on surfaces for high quality remeshing
Proceedings of the 2008 ACM symposium on Solid and physical modeling
Spectral quadrangulation with orientation and alignment control
ACM SIGGRAPH Asia 2008 papers
Capacity-constrained point distributions: a variant of Lloyd's method
ACM SIGGRAPH 2009 papers
Multi-class blue noise sampling
ACM SIGGRAPH 2010 papers
Parallel Poisson disk sampling with spectrum analysis on surfaces
ACM SIGGRAPH Asia 2010 papers
Anisotropic blue noise sampling
ACM SIGGRAPH Asia 2010 papers
Spectral sampling of manifolds
ACM SIGGRAPH Asia 2010 papers
Point sampling with general noise spectrum
ACM Transactions on Graphics (TOG) - SIGGRAPH 2012 Conference Proceedings
Applications of Geometry Processing: Blue noise sampling of surfaces
Computers and Graphics
Analysis and synthesis of point distributions based on pair correlation
ACM Transactions on Graphics (TOG) - Proceedings of ACM SIGGRAPH Asia 2012
Blue noise through optimal transport
ACM Transactions on Graphics (TOG) - Proceedings of ACM SIGGRAPH Asia 2012
Fourier analysis of stochastic sampling strategies for assessing bias and variance in integration
ACM Transactions on Graphics (TOG) - SIGGRAPH 2013 Conference Proceedings
Line segment sampling with blue-noise properties
ACM Transactions on Graphics (TOG) - SIGGRAPH 2013 Conference Proceedings
Blue noise sampling with controlled aliasing
ACM Transactions on Graphics (TOG)
An approach to segmentation of mouse brain images via intermodal registration
Pattern Recognition and Image Analysis
ACM Transactions on Graphics (TOG)
Gap processing for adaptive maximal poisson-disk sampling
ACM Transactions on Graphics (TOG)
Partition of unity parametrics for texture synthesis
Proceedings of Graphics Interface 2013
Improving spatial coverage while preserving the blue noise of point sets
Computer-Aided Design
Fast adaptive blue noise on polygonal surfaces
Graphical Models
Special Section on Graphics Interface: Texture synthesis using label assignment over a graph
Computers and Graphics
Hi-index | 0.00 |
Sampling is a core component for many graphics applications including rendering, imaging, animation, and geometry processing. The efficacy of these applications often crucially depends upon the distribution quality of the underlying samples. While uniform sampling can be analyzed by using existing spatial and spectral methods, these cannot be easily extended to general non-uniform settings, such as adaptive, anisotropic, or non-Euclidean domains. We present new methods for analyzing non-uniform sample distributions. Our key insight is that standard Fourier analysis, which depends on samples' spatial locations, can be reformulated into an equivalent form that depends only on the distribution of their location differentials. We call this differential domain analysis. The main benefit of this reformulation is that it bridges the fundamental connection between the samples' spatial statistics and their spectral properties. In addition, it allows us to generalize our method with different computation kernels and differential measurements. Using this analysis, we can quantitatively measure the spatial and spectral properties of various non-uniform sample distributions, including adaptive, anisotropic, and non-Euclidean domains.