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