Surface Reconstruction from Arbitrarily Large Point Clouds

Abstract

Generating 3D robotic maps from point cloud data is an active field of research. To handle high resolution data from terrestrial laser scanning to generate maps for mobile robots is still challenging, especially for city scale environments. In this short paper, we present the results of an approach for surface reconstruction from arbitrarily large point clouds. To achieve this, we serialize the large input data into suitable chunks, that are serialized to a shared hard drive. After computation, the partial results are fused into a globally consistent reconstruction.