PixelPie: Maximal Poisson-disk Sampling with Rasterization
"PixelPie: Maximal Poisson-disk Sampling with Rasterization"
Cheuk Yiu Ip (University of Maryland), M. Adil Yalçin (University of Maryland), David Luebke (NVIDIA), Amitabh Varshney (University of Maryland), in High Performance Graphics 2013, July 2013
|Research Area:||3D Graphics|
|Author(s):||Cheuk Yiu Ip (University of Maryland), M. Adil Yalçin (University of Maryland), David Luebke (NVIDIA), Amitabh Varshney (University of Maryland)|
|Abstract:||We present PixelPie, a highly parallel geometric formulation of the Poisson-disk sampling problem on the graphics pipeline. Traditionally, generating a distribution by throwing darts and removing conflicts has been viewed as an inherently sequential process. In this paper, we present an efficient Poisson-disk sampling algorithm that uses rasterization in a highly parallel manner. Our technique is an iterative two step process. The first step of each iteration involves rasterization of random darts at varying depths. The second step involves culling conflicted darts. Successive iterations identify and fill in the empty regions to obtain maximal distributions. Our approach maps well to the parallel and optimized graphics functions on the GPU and can be easily extended to perform importance sampling. Our implementation can generate Poisson-disk samples at the rate of nearly 7 million samples per second on a GeForce GTX 580 and is significantly faster than the state-of-the-art maximal Poisson-disk sampling techniques.|
ACM Copyright Notice Copyright by the Association for Computing Machinery, Inc. Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, to republish, to post on servers, or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from Publications Dept, ACM Inc., fax +1 (212) 869-0481, or email@example.com. The definitive version of this paper can be found at ACM's Digital Library http://www.acm.org/dl/.