A fast algorithm for approximate surface reconstruction from sampled points

Abstract

► A new algorithm for fast approximate surface reconstruction from sampled points is presented. ► Voxel matrix dimensions are automatically computed using proposed heuristics. ► We compare the reconstruction algorithm with several existing reconstruction algorithms. ► We evaluate approximated surface error as well as the time complexity. This paper presents a new algorithm for fast approximate surface reconstruction from sampled points. This algorithm works over three steps. Firstly, a raw rectangular surface is obtained, and then this surface is triangulated and smoothed in the second step. The surface vertices are fitted to the nearest input points at the end. The algorithm is very fast, numerically stable, easy to implement, and it constructs a watertight surface. In the experimental section, the algorithm is compared with other available algorithms (algorithm from CGAL library, Power Crust, Tight cocone, and Poisson reconstruction) in regards to the spent CPU time. Finally, an error of the obtained approximate surface is empirically estimated.