计算机工程 ›› 2019, Vol. 45 ›› Issue (1): 264-269,277.doi: 10.19678/j.issn.1000-3428.0048705

• 图形图像处理 • 上一篇    下一篇

基于最优传输的网格参数化序列簇生成方法

夏诗羽,苏科华,陈彩玲   

  1. 武汉大学 计算机学院,武汉 430072
  • 收稿日期:2017-09-18 出版日期:2019-01-15 发布日期:2019-01-15
  • 作者简介:夏诗羽(1993—),女,硕士研究生,主研方向为计算共形几何;苏科华,副教授、博士;陈彩玲,硕士研究生。
  • 基金项目:

    国家自然科学基金(61772379)

Grid Parameterized Sequence Clusters Generation Method Based on Optimal Transmission

XIA Shiyu,SU Kehua,CHEN Cailing   

  1. School of Computer Science,Wuhan University,Wuhan 430072,China
  • Received:2017-09-18 Online:2019-01-15 Published:2019-01-15

摘要:

利用Ricci曲率流将原曲面上的面元测度前推到目标参数域上形成初始面元测度,对初始面元测度或目标面元测度进行变换,以构造一系列连续变换的面元测度序列,然后计算面元测度间的最优传输映射并构建连续变换的参数化序列簇。通过莫比乌斯变换、曲率强化和重要性驱动3种方式对面元测度进行变换实验,结果表明,相比拟等积方法,该方法可以构造出多种不同的参数化序列簇,并能取得较好的特殊参数化效果。

关键词: 参数化序列簇, 最优传输映射, Ricci曲率流, 测度控制, 莫比乌斯变换

Abstract:

Using Ricci curvature flow,the original surface panel measure is pushed forward to the target parameter domain to form the initial panel measure.After transforming the initial panel measure or the target panel measure,a series of continuous transformation panel measure sequences are constructed.Then the parameterized sequence clusters of continuous transformation is constructed by calculating the optimal transmission mapping between the panel measures.The transformation experiments are carried out by using Moebius transformation,curvature reinforcement and importance drive,and results show that compared with the Quasi-area method,this method can construct a variety of different parameterized sequence clusters and achieve better special parameterized effect.

Key words: parameterized sequence clusters, optimal transmission mapping, Ricci curvature flow, measure control, Moebius transformation

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