Fast PDE approach to surface reconstruction from large cloud of points

In this article we propose an algorithm for fast reconstruction of 3D surfaces starting from large sets of unorganized sample points. The proposed algorithm is based on the temporal evolution of a volumetric implicit function. The evolving front can be thought as the surface that separates two different fluids obeying specific fluid dynamics laws. One remarkable feature of this approach is its ability to model complex topologies using a set of intuitive tools derived from fluid physics: Global and local surface descriptors are used allowing the parallelization of the algorithm on different processes each of one can operate on different sub-sets of the whole cloud with different resolutions and accuracies. Tests on large and complex clouds of 3D points show an high efficiency of the proposed approach: between one and two orders of magnitude faster than traditional implicit solutions.