FAST SEMANTIC SEGMENTATION OF 3D POINT CLOUDS WITH STRONGLY VARYING DENSITY

FAST SEMANTIC SEGMENTATION OF 3D POINT CLOUDS WITH STRONGLY VARYING DENSITY

We describe an effective and efficient method for point-wise semantic classification of 3D point clouds. The method can handle unstructured and inhomogeneous point clouds such as those derived from static terrestrial LiDAR or photogammetric reconstruction; and it is computationally efficient, making...

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Bibliographic Details
Main Authors:	T. Hackel, J. D. Wegner, K. Schindler
Format:	Article
Language:	English
Published:	Copernicus Publications 2016-06-01
Series:	ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Online Access:	http://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/III-3/177/2016/isprs-annals-III-3-177-2016.pdf

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