Title :
Automatic extraction of salient geometric entities from LIDAR point clouds
Author :
Auer, Stefan ; Hinz, Stefan
Author_Institution :
Tech. Univ. Muenchen, Muenchen
Abstract :
This paper introduces a modularized tool for the processing of LIDAR data based on the analysis of neighbor relationships between LIDAR points with the goal to extract planes, lines, and points in 3D. The tool\´s functionalities will be exemplified by the application of reconstructing building roofs. Detecting buildings within digital surface models is one further step to enhance the results of fully- and semi-automatic software tools which handle huge LIDAR point clouds. The functionalities comprise the sorting of point coordinates to improve efficiency, the retrieval of LIDAR point topology by triangulation of points, the extraction of 3D planes by "plane growing" and the determination of lines, points and roof outlines based on the 3D planes by statistical estimation and hypothesis testing of their parameters.
Keywords :
feature extraction; image reconstruction; object detection; optical radar; remote sensing by laser beam; stereo image processing; terrain mapping; 3D plane extraction; LIDAR data processing; LIDAR point clouds; LIDAR point topology retrieval; building detection; building roof reconstruction; digital surface model; hypothesis testing; neighbor relationship analysis; plane growing; point coordinates; point triangulation; salient geometric entity extraction; statistical estimation; Clouds; Data mining; Digital elevation models; Geographic Information Systems; Laser modes; Laser radar; Solid modeling; Sorting; Surface reconstruction; Topology; LIDAR; Modeling; Reconstruction; Region Growing; Roof Extraction; Three-Dimensional;
Conference_Titel :
Geoscience and Remote Sensing Symposium, 2007. IGARSS 2007. IEEE International
Conference_Location :
Barcelona
Print_ISBN :
978-1-4244-1211-2
Electronic_ISBN :
978-1-4244-1212-9
DOI :
10.1109/IGARSS.2007.4423353