CASIA OpenIR  > 模式识别国家重点实验室  > 多媒体计算与图形学
全卫泽; 郭建伟; 张义宽; 孟维亮; 张晓鹏; 严冬明
Source PublicationSCIENTIA SINICA Informationis
Other Abstract最大化泊松圆盘采样(Maximal Poisson-disk Sampling--MPS)是计算机图形学领域的一个基础研究问题。一个理想的采样点集应该满足无偏差采样性质,最小距离属性和最大化性质。传统的最大化泊松圆盘采样一般通过投镖法(Dart Throwing)来实现,但是众所周知,该方法的不足之处在于无法精确控制采样点数目。针对该问题,本文提出了一种新的方法可以实现精确控制二维等半径最大化泊松圆盘采样的点数并且同时满足其它性质。与已有方法不同的是,本文提出的方法通过调整采样半径达到控制采样点数的目的。首先,根据用户指定的采样点数目和采样区域(闭合的多边形)生成随机点集,并进行Delaunay三角化,并且将当前三角化中的最短边长作为当前的采样半径;接着,迭代地移除全局最短边中邻域平均边长较大的采样点,然后采用投镖法将其随机插入到以当前采样半径计算得到的空隙区域内。通过迭代地调整采样点的位置,采样半径不断增大,从而最后实现固定点数的最大化泊松圆盘采样。大量实验结果表明,该方法可以得到高质量的采样点集,同时很好地保持了采样点集的蓝噪声性质。;
In the eld of computer graphics, Maximal Poisson-disk Sampling (MPS) is a fundamental research
topic. An ideal sampling set should satisfy unbiased sampling property, minimal distance property, and maximal
sampling property. In general, MPS is obtained by Dart Throwing§as we all know§the drawback of this method
is unable to precisely control the number of samples. In view of the above problem, this work proposes a novelty
algorithm that can precisely control the number of samples of two-dimensional radius-equal MPS, and satisfy
other properties simultaneously. Unlike existing methods, the proposed method controls the number of samples
by adjusting sampling radius. Firstly, according to user-speci ed the number of samples and sampling domain
(closed polygon), initial samples are randomly obtained, then Delaunay triangulation is conducted, and taking as
current sampling radius the shortest edge length of the triangulation. Secondly, iteratively removing the endpoint
of global shortest edge with larger neighborhood-averaged edge length, and then using Dart Throwing to randomly
insert it into Gap region that is calculated at current sampling radius. By iteratively adjusting the position of
points, the sampling radius increases gradually, nally, MPS with xed number of sampling point can be achieved.
Experimental results show that this metho
Document Type期刊论文
Recommended Citation
GB/T 7714
全卫泽,郭建伟,张义宽,等. 基于采样半径优化的最大化泊松圆盘采样[J]. SCIENTIA SINICA Informationis,2017,47(4):442-454.
APA 全卫泽,郭建伟,张义宽,孟维亮,张晓鹏,&严冬明.(2017).基于采样半径优化的最大化泊松圆盘采样.SCIENTIA SINICA Informationis,47(4),442-454.
MLA 全卫泽,et al."基于采样半径优化的最大化泊松圆盘采样".SCIENTIA SINICA Informationis 47.4(2017):442-454.
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