Feature Extraction of Buildings Based on Vehicle-borne LiDAR Data

DOI

10.2991/rsete.2013.20How to use a DOI?

Keywords

vehicle-borne LiDAR, point cloud classification, feature extraction, building modeling

Abstract

Vehicle-borne LiDAR is a new technical means to quickly obtain high precision three-dimensional data for the city modeling and digital city construction. But the data are discrete and no topological relations. So this research is focused on the vehicular laser-scanning system to obtain the feature lines of buildings. First of all, the point cloud data of surface features are classified, and then the building feature points are extracted successfully by the way of horizontal projection and section search. Using linear regression model verifies that the feature points of the different sections can fit to characteristic line of linear significant. Under the premise of ensuring the accuracy, this method can be achieved of the extraction of the feature points of buildings and of the classification of ground objects.

Copyright

© 2013, 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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TY  - CONF
AU  - Sheng Lin
AU  - Wang Shuangting
AU  - Zhou Gaowei
PY  - 2013/08
DA  - 2013/08
TI  - Feature Extraction of Buildings Based on Vehicle-borne LiDAR Data
BT  - Proceedings of the 2013 the International Conference on Remote Sensing, Environment and Transportation Engineering (RSETE 2013)
PB  - Atlantis Press
SP  - 78
EP  - 81
SN  - 1951-6851
UR  - https://doi.org/10.2991/rsete.2013.20
DO  - 10.2991/rsete.2013.20
ID  - Lin2013/08
ER  -