A Fast Surface Reconstruction Algorithm for Noisy 3D Unorganized Points

摘要

Advanced 3D scanning technologies enable us to obtain dense and accurate surface sample point sets. From sufficiently dense sample point set, Crust algorithm, which is based on Voronoi diagram and its dual Delaunay triangulation, can reconstruct a triangle mesh that is topologically valid and convergent to the original surface. However, the algorithm is restricted in the practical application because of its long running time, and when the point cloud must not be nosiy, the surface reconstructed is not good. This paper proposes a improved method of fuzzy c-means clustering to delete the noisy points and a non-uniformly sampling method to resample the input data set according to the local feature size before reconstruction. In this way, we increase the speed of reconstruction for noisy points without losing the details we need.