Proceedings of the 2016 3rd International Conference on Mechatronics and Information Technology

An Automatic Building Reconstruction Method from Airborne LiDAR Data and Maps

Authors
Jing Li, Siqi Xu, Wei Zhang, Yin Huang, Ping Gao
Corresponding Author
Jing Li
Available Online April 2016.
DOI
10.2991/icmit-16.2016.44How to use a DOI?
Keywords
airborne LiDAR; building boundary; building reconstruction; normal segmentation
Abstract

To the problem of poor efficiency and low accuracy of building reconstruction method, an automatic building reconstruction method from airborne LiDAR point clouds and building outline from GIS maps is proposed. This article discusses the key steps of building reconstruction such as the buildings extraction, roof segmentation, roof structural line extraction, topology reconstruction and model generation. Finally, to verify the effectiveness and availability of the various steps, a real experiment proved that this method can quickly rebuild a more complex model of city buildings.

Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2016 3rd International Conference on Mechatronics and Information Technology
Series
Advances in Computer Science Research
Publication Date
April 2016
ISBN
10.2991/icmit-16.2016.44
ISSN
2352-538X
DOI
10.2991/icmit-16.2016.44How to use a DOI?
Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Jing Li
AU  - Siqi Xu
AU  - Wei Zhang
AU  - Yin Huang
AU  - Ping Gao
PY  - 2016/04
DA  - 2016/04
TI  - An Automatic Building Reconstruction Method from Airborne LiDAR Data and Maps
BT  - Proceedings of the 2016 3rd International Conference on Mechatronics and Information Technology
PB  - Atlantis Press
SP  - 247
EP  - 256
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmit-16.2016.44
DO  - 10.2991/icmit-16.2016.44
ID  - Li2016/04
ER  -