Lv Chenlei, Lin Weisi, Zheng Jianmin
IEEE Trans Vis Comput Graph. 2024 Jul;30(7):3196-3209. doi: 10.1109/TVCG.2022.3227970. Epub 2024 Jun 27.
With the development of 3D digital geometry technology, 3D triangular meshes are becoming more useful and valuable in industrial manufacturing and digital entertainment. A high quality triangular mesh can be used to represent a real world object with geometric and physical characteristics. While anisotropic meshes have advantages of representing shapes with sharp features (such as trimmed surfaces) more efficiently and accurately, isotropic meshes allow more numerically stable computations. When there is no anisotropic mesh requirement, isotropic triangles are always a good choice. In this paper, we propose a remeshing method to convert an input mesh into an adaptively isotropic one based on a curvature smoothed field (CSF). With the help of the CSF, adaptively isotropic remeshing can retain the curvature sensitivity, which enables more geometric features to be kept, and avoid the occurrence of obtuse triangles in the remeshed model as much as possible. The remeshed triangles with locally isotropic property benefit various geometric processes such as neighbor-based feature extraction and analysis. The experimental results show that our method achieves better balance between geometric feature preservation and mesh quality improvement compared to peers. We provide the implementation codes of our resampling method at github.com/vvvwo/Adaptively-Isotropic-Remeshing.
随着3D数字几何技术的发展,3D三角形网格在工业制造和数字娱乐领域变得越来越有用和有价值。高质量的三角形网格可用于表示具有几何和物理特征的现实世界物体。虽然各向异性网格具有更高效、准确地表示具有尖锐特征(如修剪曲面)形状的优点,但各向同性网格允许更数值稳定的计算。当没有各向异性网格要求时,各向同性三角形始终是一个不错的选择。在本文中,我们提出了一种重新网格化方法,基于曲率平滑场(CSF)将输入网格转换为自适应各向同性网格。借助CSF,自适应各向同性重新网格化可以保留曲率敏感性,从而能够保留更多几何特征,并尽可能避免在重新网格化模型中出现钝角三角形。具有局部各向同性属性的重新网格化三角形有利于各种几何处理,如基于邻域的特征提取和分析。实验结果表明,与同行相比,我们的方法在几何特征保留和网格质量改进之间实现了更好的平衡。我们在github.com/vvvwo/Adaptively-Isotropic-Remeshing上提供了我们重采样方法的实现代码。