Authors:
Helmi Ben Hmida
1
;
Christophe Cruz
2
;
Frank Boochs
3
and
Christophe Nicolle
2
Affiliations:
1
Fachhochschule Mainz, Laboratoire Le2i and UMR-5158 CNRS, Germany
;
2
Laboratoire Le2i and UMR-5158 CNRS, France
;
3
Fachhochschule Mainz, Germany
Keyword(s):
Geometric analysis, Topologic analysis, 3D processing algorithm, Semantic web, Knowledge modelling, Ontology, 3D scene reconstruction, Object identification.
Related
Ontology
Subjects/Areas/Topics:
Applications and Case-studies
;
Artificial Intelligence
;
Biomedical Engineering
;
Data Engineering
;
Enterprise Information Systems
;
Enterprise Software Technologies
;
Expert Systems
;
Health Information Systems
;
Information Systems Analysis and Specification
;
Intelligent Problem Solving
;
Knowledge Acquisition
;
Knowledge Engineering and Ontology Development
;
Knowledge-Based Systems
;
Ontologies and the Semantic Web
;
Ontology Engineering
;
Software Engineering
;
Symbolic Systems
Abstract:
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.