Distributed Surface Reconstruction

Abstract

Recent advancements in scanning technologies and their rise in availability have shifted the focus from reconstructing surfaces from point clouds of small areas to large, e.g., city-wide scenes, containing massive amounts of data. We adapt a surface reconstruction method to work in a distributed fashion on a high-performance cluster, reconstructing datasets with millions of vertices in seconds by exploiting the locality of the connectivity required by the reconstruction algorithm to efficiently divide-and-conquer the problem of creating triangulations from very large unstructured point clouds.