Merging overlapping depth maps into a nonredundant point cloud

Abstract

Combining long sequences of overlapping depth maps without simplification results in a huge number of redundant points, which slows down further processing. In this paper, a novel method is presented for incrementally creating a nonredundant point cloud with varying levels of detail without limiting the captured volume or requiring any parameters from the user. Overlapping measurements are used to refine point estimates by reducing their directional variance. The algorithm was evaluated with plane and cube fitting residuals, which were improved considerably over redundant point clouds. © 2013 Springer-Verlag.