  This paper presents a knowledge-based detection of objects approach using the
OWL ontology language, the Semantic Web Rule Language, and 3D processing
built-ins aiming at combining geometrical analysis of 3D point clouds and
specialist's knowledge. This combination allows the detection and the
annotation of objects contained in point clouds. The context of the study is
the detection of railway objects such as signals, technical cupboards, electric
poles, etc. Thus, the resulting enriched and populated ontology, that contains
the annotations of objects in the point clouds, is used to feed a GIS systems
or an IFC file for architecture purposes.
