Paper Info
Title
Knowledge Base Approach for 3D Objects Detection in Point Clouds Using 3D Processing and Specialists Knowledge
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. Here, we share our experience regarding the creation of 3D semantic facility model out of unorganized 3D point clouds. Thus, a knowledge-based detection approach of objects using the OWL ontology language is presented. This knowledge is used to define SWRL detection rules. In addition, the combination of 3D processing built-ins and topological Built-Ins in SWRL rules allows a more flexible and intelligent detection, and the annotation of objects contained in 3D point clouds. The created WiDOP prototype takes a set of 3D point clouds as input, and produces as output a populated ontology corresponding to an indexed scene visualized within VRML language. The context of the study is the detection of railway objects materialized within the Deutsche Bahn scene 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 system or an IFC file for architecture purposes.
Year
Venue
Keywords
2013
International journal on advances in intelligent systems
geometric analysis,ontology,semantic web
Field
DocType
Volume
Ontology (information science),Ontology,Data mining,VRML,Computer science,OWL-S,Knowledge base,Point cloud,Semantic Web Rule Language,Web Ontology Language
Journal
abs/1301.4991
ISSN
Citations 
PageRank 
International Journal On Advances in Intelligent Systems 5, 1 et 2 (2012) 1-14
2
0.36
References 
Authors
0
4
Name
Order
Citations
PageRank
Helmi Ben Hmida172.79
Christophe Cruz2298.10
Frank Boochs34312.60
Christophe Nicolle420.70