Voting for Distortion Points in Geometric Processing

Low isometric distortion is often required for mesh parameterizations. A configuration of some vertices, where the concentrated, provides a way to mitigate distortion, but determining number and placement these vertices non-trivial. We call points. present novel automatic method detect points using voting strategy. Our integrates two components: candidate generation voting. Given closed triangular mesh, we generate by executing three-step procedure repeatedly: (1) randomly cut an input disk topology; (2) compute low conformal parameterization; (3) Finally, count final demonstrate that our algorithm succeeds when employed on various meshes with genus zero or higher. The generated are utilized in three applications, including planar parameterization, semi-automatic landmark correspondence, isotropic remeshing. Compared other state-of-the-art methods, demonstrates stronger practical robustness point detection.