Input size independent efficient quality meshing of the interior of 2D point cloud data

作     者：Singh, Neha Ray, Tathagata Parimi, Chandu Kuchibhotla, Srivastava 

作者机构：Birla Inst Technol & Sci Pilani Dept Comp Sci & Informat Syst Hyderabad Campus Hyderabad Telangana India Birla Inst Technol & Sci Pilani Dept Civil Engn Hyderabad Campus Hyderabad Telangana India 

出 版 物：《JOURNAL OF COMPUTATIONAL DESIGN AND ENGINEERING》 (J. Comput. Des. Eng.)

年 卷 期：2019年第6卷第3期

页      面：316-326页

核心收录：

学科分类：08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：Birla Institute of Technology and Science  Pilani 

主　　题：Mesh generation Delaunay triangulation Point cloud data Curve reconstruction Pre-processing techniques 

摘      要：This paper describes a framework to generate an unstructured Delaunay mesh of a two-dimensional domain whose boundary is specified by a point cloud data (PCD). The assumption is that the PCD is sampled from a smooth 1-manifold without a boundary definition and is significantly dense (at least epsilon-sampled where epsilon 1). Presently meshing of such a domain requires two explicit steps, namely the extraction of model definition from the PCD and the use of model definition to guide the unstructured mesh generation. For a densely sampled PCD, the curve reconstruction process is dependent on the size of input PCD and can become a time-consuming overhead. We propose an optimized technique that bypasses the explicit step of curve reconstruction by implicit access to the model information from a well-sampled PCD. A mesh thus generated will be optimal, as the fineness of the mesh is not dictated by the sampling of PCD, but only the geometric complexity of the underlying curve. The implementation and experiments of the proposed framework show significant improvement in expense over the traditional methodology. The main contribution of this paper is the circumvention of the explicit time-consuming step of boundary computation which is a function of the PCD sampling size and a direct generation of a mesh whose complexity is dictated by the geometry of the domain. (C) 2018 Society for Computational Design and Engineering. Publishing Services by Elsevier.