On a knowledge-based approach to the classification of mobile laser scanning point clouds

Journal Article (2018)
Author(s)

M.J.P.M. Lemmens (TU Delft - OLD Department of GIS Technology)

Research Group
OLD Department of GIS Technology
Copyright
© 2018 M.J.P.M. Lemmens
DOI related publication
https://doi.org/10.5194/isprs-archives-XLII-4-343-2018
More Info
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Publication Year
2018
Language
English
Copyright
© 2018 M.J.P.M. Lemmens
Research Group
OLD Department of GIS Technology
Issue number
4
Volume number
42
Pages (from-to)
411-416
Reuse Rights

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Abstract

A knowledge-based system exploits the knowledge, which a human expert uses for completing a complex task, through a database containing decision rules, and an inference engine. Already in the early nineties knowledge-based systems have been proposed for automated image classification. Lack of success faded out initial interest and enthusiasm, the same fate neural networks struck at that time. Today the latter enjoy a steady revival. This paper aims at demonstrating that a knowledge-based approach to automated classification of mobile laser scanning point clouds has promising prospects. An initial experiment exploiting only two features, height and reflectance value, resulted in an overall accuracy of 79% for the Paris-rue-Madame point cloud bench mark data set.