Print Email Facebook Twitter Towards automatic semantic labelling of 3D city models Title Towards automatic semantic labelling of 3D city models Author Rook, Merwin Biljecki, F. (TU Delft Urban Data Science) Diakite, A.A. (TU Delft Urban Data Science) Contributor Dimopoulou, E. (editor) van Oosterom, P. (editor) Date 2016 Abstract The lack of semantic information in many 3D city models is a considerable limiting factor in their use, as a lot of applications rely on semantics. Such information is not always available, since it is not collected at all times, it might be lost due to data transformation, or its lack may be caused by non-interoperability in data integration from other sources. This research is a first step in creating an automatic workflow that semantically labels plain 3D city model represented by a soup of polygons, with semantic and thematic information, as defined in the CityGML standard. The first step involves the reconstruction of the topology, which is used in a region growing algorithm that clusters upward facing adjacent triangles. Heuristic rules, embedded in a decision tree, are used to compute a likeliness score for these regions that either represent the ground (terrain) or a RoofSurface. Regions with a high likeliness score, to one of the two classes, are used to create a decision space, which is used in a support vector machine (SVM). Next, topological relations are utilised to select seeds that function as a start in a region growing algorithm, to create regions of triangles of other semantic classes. The topological relationships of the regions are used in the aggregation of the thematic building features. Finally, the level of detail is detected to generate the correct output in CityGML. The results show an accuracy between 85 % and 99 % in the automatic semantic labelling on four different test datasets. The paper is concluded by indicating problems and difficulties implying the next steps in the research. Subject 3D city modelsemanticsclassificationCityGML3D GIS To reference this document use: http://resolver.tudelft.nl/uuid:6f644912-56c7-435f-b2c2-15456821fb90 DOI https://doi.org/10.5194/isprs-annals-IV-2-W1-23-2016 Source ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, IV-2/W1 Event 11th 3D Geoinfo Conference, 2016-10-20 → 2016-10-21, Athens, Greece Part of collection Institutional Repository Document type conference paper Rights © 2016 Merwin Rook, F. Biljecki, A.A. Diakite Files PDF isprs_annals_IV_2_W1_23_2016.pdf 2.07 MB Close viewer /islandora/object/uuid:6f644912-56c7-435f-b2c2-15456821fb90/datastream/OBJ/view