We present a fast, memory efficient algorithm that generates a manifold triangular mesh S passing through a set of unorganized points Pc R3. Nothing is assumed about the geometry, topology or presence of boundaries in the data set except that P is sampled from a real manifold surface. The speed of our algorithm is derived from a projection-based approach we use to determine the incident faces on a point. We define our sampling criteria to sample the surface and guarantee a topologically correct mesh after surface reconstruction for such a sampled surface. We also present a new algorithm to find the normal at a vertex, when the surface is sampled according our given criteria. We also present results of our surface reconstruction using our algorithm on unorganized point clouds of various models.
Meenakshisundaram, Gopi, "Surface Reconstruction based on Lower Dimensional Localized Delaunay Triangulation" (2000). Link Foundation Modeling, Simulation and Training Fellowship Reports. 9.