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Blue-Noise Remeshing with Farthest Point Optimization
Yan, Dong-Ming; Guo, Jianwei; Jia, Xiaohong; Zhang, Xiaopeng; Wonka Peter
Source PublicationComputer Graphics Forum
2014
Volume33Issue:5Pages:167-176
Abstract
In this paper, we present a novel method for surface sampling and remeshing with good blue-noise properties. Our
approach is based on the farthest point optimization (FPO), a relaxation technique that generates high quality
blue-noise point sets in 2D. We propose two important generalizations of the original FPO framework: adaptive
sampling and sampling on surfaces. A simple and efficient algorithm for accelerating the FPO framework is
also proposed. Experimental results show that the generalized FPO generates point sets with excellent blue-noise
properties for adaptive and surface sampling. Furthermore, we demonstrate that our remeshing quality is superior
to the current state-of-the-art approaches.
KeywordBlue Noise Remeshing
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/14004
Collection模式识别国家重点实验室_多媒体计算与图形学
Recommended Citation
GB/T 7714
Yan, Dong-Ming,Guo, Jianwei,Jia, Xiaohong,et al. Blue-Noise Remeshing with Farthest Point Optimization[J]. Computer Graphics Forum,2014,33(5):167-176.
APA Yan, Dong-Ming,Guo, Jianwei,Jia, Xiaohong,Zhang, Xiaopeng,&Wonka Peter.(2014).Blue-Noise Remeshing with Farthest Point Optimization.Computer Graphics Forum,33(5),167-176.
MLA Yan, Dong-Ming,et al."Blue-Noise Remeshing with Farthest Point Optimization".Computer Graphics Forum 33.5(2014):167-176.
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