Abstract
Abstract—Three-dimensional (3D) models of environments are
a promising technique for serious gaming and professional
engineering applications. In this paper, we introduce a fast and
memory-efficient system for the reconstruction of large-scale
environments based on point clouds. Our main contribution
is the emphasis on the data processing of large planes, for
which two algorithms have been designed to improve the overall
performance of the 3D reconstruction. First, a flatness-based
segmentation algorithm is presented for plane detection in point
clouds. Second, a quadtree-based algorithm is proposed for
decimating the point cloud involved with the segmented plane
and consequently improving the efficiency of triangulation. Our
experimental results have shown that the proposed system and
algorithms have a high efficiency in speed and memory for
environment reconstruction. Depending on the amount of planes
in the scene, the obtained efficiency gain varies between 20%
and 50%.
Original language | English |
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Title of host publication | Proceedings of the 10th annual IEEE Consumer Communications and Networking Conference, 11-14 January 2013, Las Vegas, USA |
Place of Publication | Las Vegas, Nevada, USA |
Publisher | Institute of Electrical and Electronics Engineers |
Pages | 43-49 |
ISBN (Print) | 978-1-4673-3132-6 |
Publication status | Published - 2013 |