Knowledge Commons of Institute of Automation,CAS
Robustly computing restricted Voronoi diagrams (RVD) on thin-plate models | |
Wang, Pengfei1; Xin, Shiqing1; Tu, Changhe1; Yan, Dongming2![]() | |
发表期刊 | COMPUTER AIDED GEOMETRIC DESIGN
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ISSN | 0167-8396 |
2020-05-01 | |
卷号 | 79页码:12 |
通讯作者 | Xin, Shiqing(xinshiqing@163.com) ; Tu, Changhe(chtu@sdu.edu.cn) |
摘要 | Voronoi diagram based partitioning of a 2-manifold surface in R-3 is a fundamental operation in the field of geometry processing. However, when the input object is a thin-plate model or contains thin branches, the traditional restricted Voronoi diagrams (RVD) cannot induce a manifold structure that is conformal to the original surface. Yan et al. (2014) are the first who proposed a localized RVD (LRVD) algorithm to handle this issue. Their algorithm is based on a face-level clustering technique, followed by a sequence of bisector clipping operations. It may fail when the input model has long and thin triangles. In this paper, we propose a more elegant/robust algorithm for computing RVDs on models with thin plates or even tubular parts. Our idea is inspired by such a fact: the desired RVD must guarantee that each site dominates a single region that is topologically identical to a disk. Therefore, when a site dominates disconnected subregions, we identify those ownerless regions and re-partition them to the nearby sites using a simple and fast local Voronoi partitioning operation. For each site that dominates a tubular part, we suggest add two more sites such that the three sites are almost rotational symmetric. Our approach is easy to implement and more robust to challenging cases than the state-of-the-art approach. (C) 2020 Elsevier B.V. All rights reserved. |
关键词 | Geometry processing Restricted Voronoi diagram Thin plate Tubular shape |
DOI | 10.1016/j.cagd.2020.101848 |
关键词[WOS] | TRIANGULAR MESHES ; TESSELLATIONS ; RESOLUTION |
收录类别 | SCI |
语种 | 英语 |
资助项目 | National Natural Science Foundation of China[61772318] ; National Natural Science Foundation of China[61772016] ; National Natural Science Foundation of China[61772312] ; National Natural Science Foundation of China[61772523] ; NSFC-Zhejiang Joint Fund for the Integration of Industrialization and Informatization[U1609218] ; NSFC-Zhejiang Joint Fund for the Integration of Industrialization and Informatization[U1909210] |
项目资助者 | National Natural Science Foundation of China ; NSFC-Zhejiang Joint Fund for the Integration of Industrialization and Informatization |
WOS研究方向 | Computer Science ; Mathematics |
WOS类目 | Computer Science, Software Engineering ; Mathematics, Applied |
WOS记录号 | WOS:000533516400006 |
出版者 | ELSEVIER |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/39461 |
专题 | 多模态人工智能系统全国重点实验室_三维可视计算 |
通讯作者 | Xin, Shiqing; Tu, Changhe |
作者单位 | 1.Shandong Univ, Jinan, Peoples R China 2.Chinese Acad Sci, Inst Automat, Beijing, Peoples R China |
推荐引用方式 GB/T 7714 | Wang, Pengfei,Xin, Shiqing,Tu, Changhe,et al. Robustly computing restricted Voronoi diagrams (RVD) on thin-plate models[J]. COMPUTER AIDED GEOMETRIC DESIGN,2020,79:12. |
APA | Wang, Pengfei,Xin, Shiqing,Tu, Changhe,Yan, Dongming,Zhou, Yuanfeng,&Zhang, Caiming.(2020).Robustly computing restricted Voronoi diagrams (RVD) on thin-plate models.COMPUTER AIDED GEOMETRIC DESIGN,79,12. |
MLA | Wang, Pengfei,et al."Robustly computing restricted Voronoi diagrams (RVD) on thin-plate models".COMPUTER AIDED GEOMETRIC DESIGN 79(2020):12. |
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