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

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

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

2018

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.

Classification
Feature extraction
Knowledge-based system
Mobile laser scanning
Point clouds

http://resolver.tudelft.nl/uuid:bb377497-6e01-4028-bfa0-3b751d15b48c

https://doi.org/10.5194/isprs-archives-XLII-4-343-2018

2194-9034

International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 42 (4), 411-416

ISPRS TC IV Mid-term Symposium “3D Spatial Information Science – The Engine of Change”, 2018-10-01 → 2018-10-05, Delft, Netherlands

Institutional Repository

journal article

© 2018 M.J.P.M. Lemmens