报告题目：optimization methods for mesh generation
Meshes are becoming commonplace in a number of applications ranging from engineering to multimedia through biomedecine and geology. For rendering the quality of a mesh refers to its approximation properties. For numerical simulation a mesh is not only required to faithfully approximate the domain of simulation, but also to satisfy size as well as shape constraints. The elaboration of algorithms for automatic mesh generation is a notoriously difficult task as it involves numerous geometric components: Complex data structures and algorithms, surface approximation, robustness as well as scalability issues. The recent trend to use measurements or automatically generated domain boundaries adds even further hurdles. Armed with our experience on triangulations and algorithms, and with components from the CGAL library, we aim at devising robust algorithms for 2D, surface as well as 3D mesh generation. Our research in mesh generation primarily focuses on the generation of isotropic simplicial meshes, i.e., triangle and tetrahedral meshes. We investigate both greedy approaches based upon Delaunay refinement and filtering, and variational approaches based upon energy functionals and associated minimizers.
Wenping Wang is Professor of Computer Science at University of Hong Kong (HKU). His research covers computer graphics, geometric computing and visualization, and has published over 100 papers in these fields. He got his B.Sc. (1983) and M.Eng. (1986) at Shandong University, China, and Ph.D. (1992) at
2001), ACM Symposium on Physical and Solid Modeling (SPM 2006) and IEEE International Conference on Shape Modeling 2009.He is also conference chair of IEEE Pacific Visualization Symposium 2011.