Fast Maximal Poisson-Disk Sampling by Randomized Tiling

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Date
2017
Journal Title
Journal ISSN
Volume Title
Publisher
ACM
Abstract
It is generally accepted that Poisson disk sampling provides great properties in various applications in computer graphics. We present KD-tree based randomized tiling (KDRT), an e cient method to generate maximal Poisson-disk samples by replicating and conquering tiles clipped from a pa ern of very small size. Our method is a twostep process: rst, randomly clipping tiles from an MPS(Maximal Poisson-disk Sample) pa ern, and second, conquering these tiles together to form the whole sample plane. e results showed that this method can e ciently generate maximal Poisson-disk samples with very small trade-o in bias error. ere are two main contributions of this paper: First, a fast and robust Poisson-disk sample generation method is presented; Second, this method can be used to combine several groups of independently generated sample pa erns to form a larger one, thus can be applied as a general parallelization scheme of any MPS methods.
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@inproceedings{
10.1145:3105762.3105778
, booktitle = {
Eurographics/ ACM SIGGRAPH Symposium on High Performance Graphics
}, editor = {
Vlastimil Havran and Karthik Vaiyanathan
}, title = {{
Fast Maximal Poisson-Disk Sampling by Randomized Tiling
}}, author = {
Wang, Tong
and
Suda, Reiji
}, year = {
2017
}, publisher = {
ACM
}, ISSN = {
2079-8679
}, ISBN = {
978-1-4503-5101-0
}, DOI = {
10.1145/3105762.3105778
} }
Citation