A Dynamic Surface Reconstruction Framework for Large Unstructured Point Sets
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Date
2006
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association
Abstract
We 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.
Description
@inproceedings{10.2312:SPBG/SPBG06/017-026,
booktitle = {Symposium on Point-Based Graphics},
editor = {Mario Botsch and Baoquan Chen and Mark Pauly and Matthias Zwicker},
title = {{A Dynamic Surface Reconstruction Framework for Large Unstructured Point Sets}},
author = {Allègre, Rémi and Chaine, Raphaëlle and Akkouche, Samir},
year = {2006},
publisher = {The Eurographics Association},
ISSN = {1811-7813},
ISBN = {3-905673-32-0},
DOI = {10.2312/SPBG/SPBG06/017-026}
}