Print Email Facebook Twitter On a knowledge-based approach to the classification of mobile laser scanning point clouds Title On a knowledge-based approach to the classification of mobile laser scanning point clouds Author Lemmens, M.J.P.M. (TU Delft OLD Department of GIS Technology) Date 2018 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. Subject ClassificationFeature extractionKnowledge-based systemMobile laser scanningPoint clouds To reference this document use: http://resolver.tudelft.nl/uuid:bb377497-6e01-4028-bfa0-3b751d15b48c DOI https://doi.org/10.5194/isprs-archives-XLII-4-343-2018 ISSN 2194-9034 Source International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 42 (4), 411-416 Event ISPRS TC IV Mid-term Symposium “3D Spatial Information Science – The Engine of Change”, 2018-10-01 → 2018-10-05, Delft, Netherlands Part of collection Institutional Repository Document type journal article Rights © 2018 M.J.P.M. Lemmens Files PDF isprs_archives_XLII_4_343_2018.pdf 1.33 MB Close viewer /islandora/object/uuid:bb377497-6e01-4028-bfa0-3b751d15b48c/datastream/OBJ/view