Classification of mobile laser scanning point clouds of urban scenes exploiting cylindrical neighbourhoods

Conference paper (2018)

Authors

M. Zheng Wuhan University, OLD Department of GIS Technology
M.J.P.M. Lemmens OLD Department of GIS Technology
P.J.M. van Oosterom OLD Department of GIS Technology
Research Group
OLD Department of GIS Technology
Copyright: © 2018 M. Zheng, M.J.P.M. Lemmens, P.J.M. van Oosterom
DOI
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https://doi.org/10.5194/isprs-archives-XLII-2-1225-2018
Point clouds Classification Feature extraction Mobile laser scanning 3D Mapping Cylindrical Approach
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Published Date

2018

Language

English

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Research Group

OLD Department of GIS Technology

Abstract

This paper presents our work on automated classification of Mobile Laser Scanning (MLS) point clouds of urban scenes with features derived from cylinders around points of consideration. The core of our method consists of spanning up a cylinder around points and deriving features, such as reflectance, height difference, from the points present within the cylindrical neighbourhood. Crucial in the approach is the selection of features from the points within the cylinder. An overall accuracy could be achieved, exploiting two bench mark data sets (Paris-rue-Madame and IQmulus & TerraMobilita) of 83% and 87% respectively.