在不可定向的流形网格曲面上计算测地距离的一般方法

不可定向的流形曲面不仅在拓扑学中占据重要的地位,在可视化和极小曲面等问题中也有很多的应用.从拓扑学的观点来看,二流形曲面的每个局部与圆盘同胚,该性质与曲面的全局可定向性无关.但在离散化的网格表示上,可定向的二流形曲面常用半边结构来表达,而不可定向的二流形曲面大多表达成若干多边形的集合,这给以可定向网格曲面为主要研究对象的数字几何处理带来很多不便.本文提出了把不可定向的二流形网格曲面上的测地距离问题转化到可定向曲面上进行处理的一般算法框架.该框架有望在不可定向的二流形网格曲面与传统数字几何处理方法之间搭起一座桥梁.为了展示该算法框架的普适性,本文将其应用于不可定向曲面上的三个重要场合,包括测地距离的求解、离散指数映射和最远点采样.

A unified framework for computing geodesic distances on nonorientable manifold polyhedral surfaces

Nonorientable manifold surfaces not only play an important role in topology, but also have numerous applications in many topics such as visualization and computation of minimal surfaces. From the topological point of view, a 2-manifold surface is locally homeomorphic to an open disk. This property is independent of the global orientability. However, as far as the discrete representation is concerned, orientable manifold surfaces are usually discretized with halfedge data structure, while nonorientable surfaces are discretized into polygon soups, which is inconvenient for digital geometry processing that often takes orientable meshes as input. In this paper, we propose a unified framework for transforming geodesic distance problems defined on nonorientable 2-manifold meshes to the counter-parts on orientable surfaces, and thereby bridging up nonorientable 2-manifold meshes and conventional geometric algorithms. In order to illustrate the universal adaptability, we apply this new approach to study three problems on nonorientable meshes, including computing exact geodesic paths, discrete exponential mapping and farthest point sampling.