Title
Multi-class anisotropic blue noise sampling for discrete element pattern generation.
Abstract
We present an element placement method for generating patterns containing \"discrete elements\". By extending various blue noise sampling methods, we propose a visually uniform distribution of multi-class elements. Our method also supports tileable aperiodic distribution. Instead of actual elements, for fast calculation, we use a circular or elliptic disk as a proxy of an element when checking conflicts with nearby elements during the distribution process. The nature of our results is comparable to swatches in books, which shows that our method is capable of generating visually appealing swatches for a set of elements. The user study showed that our method outperformed state-of-the-art discrete element texture synthesis approaches in terms of pattern visual quality.
Year
DOI
Venue
2016
10.1007/s00371-016-1248-6
The Visual Computer
Keywords
Field
DocType
Blue noise sampling, Discrete element texture, Element distribution, Pattern generation
Computer vision,Anisotropy,Pattern generation,Colors of noise,Computer science,Algorithm,Uniform distribution (continuous),Theoretical computer science,Sampling (statistics),Artificial intelligence,Aperiodic graph,Texture synthesis
Journal
Volume
Issue
ISSN
32
6-8
1432-2315
Citations 
PageRank 
References 
0
0.34
18
Authors
2
Name
Order
Citations
PageRank
Naoki Kita1159.62
Kazunori Miyata216141.73