Fast Maximal Poisson-Disk Sampling by Randomized Tiling

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dc.contributor.author Wang, Tong en_US
dc.contributor.author Suda, Reiji en_US
dc.contributor.editor Vlastimil Havran and Karthik Vaiyanathan en_US
dc.date.accessioned 2017-12-06T19:47:41Z
dc.date.available 2017-12-06T19:47:41Z
dc.date.issued 2017
dc.identifier.isbn 978-1-4503-5101-0
dc.identifier.issn 2079-8679
dc.identifier.uri http://dx.doi.org/10.1145/3105762.3105778
dc.identifier.uri https://diglib.eg.org:443/handle/10.1145/3105762-3105778
dc.description.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. en_US
dc.publisher ACM en_US
dc.subject Computing methodologies Computer graphics
dc.subject Poisson
dc.subject disk Sampling
dc.title Fast Maximal Poisson-Disk Sampling by Randomized Tiling en_US
dc.description.seriesinformation Eurographics/ ACM SIGGRAPH Symposium on High Performance Graphics
dc.description.sectionheaders Real-Time Graphics Techniques
dc.identifier.doi 10.1145/3105762.3105778


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