期刊
IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS
卷 27, 期 4, 页码 2469-2480出版社
IEEE COMPUTER SOC
DOI: 10.1109/TVCG.2019.2947420
关键词
Distortion; Mesh generation; Surface treatment; Topology; Manuals; Distortion measurement; Robustness; Distortion points; parameterizations; low isometric distortion
资金
- National Natural Science Foundation of China [61802359, 61672482, 11626253]
- Anhui Provincial Natural Science Foundation [1808085QF208]
- Fundamental Research Funds for the Central Universities [WK0010460006, WK0010450004]
The algorithm proposes an automatic method for detecting distortion points using a voting strategy. It integrates candidate generation and candidate voting components and demonstrates strong practical robustness when applied to various closed meshes.
Low isometric distortion is often required for mesh parameterizations. A configuration of some vertices, where the distortion is concentrated, provides a way to mitigate isometric distortion, but determining the number and placement of these vertices is non-trivial. We call these vertices distortion points. We present a novel and automatic method to detect distortion points using a voting strategy. Our method integrates two components: candidate generation and candidate voting. Given a closed triangular mesh, we generate candidate distortion points by executing a three-step procedure repeatedly: (1) randomly cut an input to a disk topology; (2) compute a low conformal distortion parameterization; and (3) detect the distortion points. Finally, we count the candidate points and generate the final distortion points by voting. We demonstrate that our algorithm succeeds when employed on various closed meshes with a genus of zero or higher. The distortion points generated by our method are utilized in three applications, including planar parameterization, semi-automatic landmark correspondence, and isotropic remeshing. Compared to other state-of-the-art methods, our method demonstrates stronger practical robustness in distortion point detection.
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