The Reconstruction of Large Three-dimensional Meshes

Surface reconstruction is the process of creating virtual three-dimensional representations of real-world objects using data obtained from 3D scanners. The traditional challenges of surface reconstruction arise from the uncertain nature of input data. Inaccuracies in scanning devices create noisy data. Point sampling is often non-uniform. And, accessibility constraints during the scanning process may leave some regions of the surface devoid of data. Robustly constructing a surface in the presence of these data anomalies is a difficult problem. In addition, surface reconstruction methods have recently encountered a new challenge resulting from developments in 3D scanning techniques. New scanning technologies have driven a dramatic increase in the size of datasets available for surface reconstruction, with datasets now exceeding one billion point samples. As a result, space and time efficiency have become critical in the development of effective reconstruction algorithms, and the design of streaming and parallel techniques has become indispensable. In this dissertation we describe a new technique for surface reconstruction, ii