参数曲面的映射独立三角化

M. Attene, B. Falcidieno, M. Spagnuolo, G. Wyvill
{"title":"参数曲面的映射独立三角化","authors":"M. Attene, B. Falcidieno, M. Spagnuolo, G. Wyvill","doi":"10.1109/SMI.2002.1003530","DOIUrl":null,"url":null,"abstract":"Typical methods for the triangulation of parametric surfaces use a sampling of the parameter space, and the wrong choice of parameterization can spoil a triangulation or even cause the algorithm to fail. We present a new method that uses a local tessellation primitive for almost-uniformly sampling and triangulating a surface, so that its parameterization becomes irrelevant. If sampling density or triangle shape has to be adaptive, the uniform mesh can be used either as an initial coarse mesh for a refinement process, or as a fine mesh to be reduced.","PeriodicalId":267347,"journal":{"name":"Proceedings SMI. Shape Modeling International 2002","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2002-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Mapping independent triangulation of parametric surfaces\",\"authors\":\"M. Attene, B. Falcidieno, M. Spagnuolo, G. Wyvill\",\"doi\":\"10.1109/SMI.2002.1003530\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Typical methods for the triangulation of parametric surfaces use a sampling of the parameter space, and the wrong choice of parameterization can spoil a triangulation or even cause the algorithm to fail. We present a new method that uses a local tessellation primitive for almost-uniformly sampling and triangulating a surface, so that its parameterization becomes irrelevant. If sampling density or triangle shape has to be adaptive, the uniform mesh can be used either as an initial coarse mesh for a refinement process, or as a fine mesh to be reduced.\",\"PeriodicalId\":267347,\"journal\":{\"name\":\"Proceedings SMI. Shape Modeling International 2002\",\"volume\":\"6 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2002-05-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings SMI. Shape Modeling International 2002\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SMI.2002.1003530\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings SMI. Shape Modeling International 2002","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SMI.2002.1003530","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6

摘要

参数曲面三角剖分的典型方法是对参数空间进行采样,错误的参数化选择可能会破坏三角剖分,甚至导致算法失败。我们提出了一种新的方法,使用局部镶嵌原语对一个表面进行几乎均匀的采样和三角化,使其参数化变得无关紧要。如果采样密度或三角形必须自适应,则均匀网格既可以用作初始粗网格以进行细化过程,也可以用作缩小的细网格。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Mapping independent triangulation of parametric surfaces
Typical methods for the triangulation of parametric surfaces use a sampling of the parameter space, and the wrong choice of parameterization can spoil a triangulation or even cause the algorithm to fail. We present a new method that uses a local tessellation primitive for almost-uniformly sampling and triangulating a surface, so that its parameterization becomes irrelevant. If sampling density or triangle shape has to be adaptive, the uniform mesh can be used either as an initial coarse mesh for a refinement process, or as a fine mesh to be reduced.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信