Allègre, RémiChaine, RaphaëlleAkkouche, SamirMario Botsch and Baoquan Chen and Mark Pauly and Matthias Zwicker2014-01-292014-01-2920063-905673-32-01811-7813https://doi.org/10.2312/SPBG/SPBG06/017-026We present a method to reconstruct simplified mesh surfaces from large unstructured point sets, extending recent work on dynamic surface reconstruction. The method consists of two core components: an efficient selective reconstruction algorithm, based on geometric convection, that simplifies the input point set while reconstructing a surface, and a local update algorithm that dynamically refines or coarsens the reconstructed surface according to specific local sampling constraints. We introduce a new data-structure that significantly accelerates the original selective reconstruction algorithm and makes it possible to handle point set models with millions of sample points. Our data-structure mixes a kd-tree with the Delaunay triangulation of the selected points enriched with a sparse subset of landmark sample points. This design efficiently responds to the specific spatial location issues of the geometric convection algorithm. We also develop an out-of-core implementation of the method, that permits to seamlessly reconstruct and interactively update simplified mesh surfaces from point sets that do not fit into main memory.Categories and Subject Descriptors (according to ACM CCS): I.3.5 [Computer Graphics]: Computational Geometry and Object Modeling