Outdoor Obstacles Detection and Localisation ...
Type de document :
Communication dans un congrès avec actes
Titre :
Outdoor Obstacles Detection and Localisation with Monovision and 3D Geographical Database
Auteur(s) :
Cappelle, Cindi [Auteur]
Laboratoire d'Automatique, Génie Informatique et Signal [LAGIS]
Badaoui, Maan [Auteur]
Systèmes Tolérants aux Fautes [STF]
Charpillet, François [Auteur]
Pormski, Denis [Auteur]
Laboratoire d'Automatique, Génie Informatique et Signal [LAGIS]
Laboratoire d'Automatique, Génie Informatique et Signal [LAGIS]
Badaoui, Maan [Auteur]
Systèmes Tolérants aux Fautes [STF]
Charpillet, François [Auteur]
Pormski, Denis [Auteur]
Laboratoire d'Automatique, Génie Informatique et Signal [LAGIS]
Titre de la manifestation scientifique :
IEEE International Conference on intelligent Transportation Systems
Ville :
Seattle
Pays :
Etats-Unis d'Amérique
Date de début de la manifestation scientifique :
2007-09-30
Éditeur :
IEEE Intelligent Transportation Systems Society
Date de publication :
2007
Discipline(s) HAL :
Informatique [cs]/Intelligence artificielle [cs.AI]
Résumé en anglais : [en]
In this paper, an obstacle detection approach for downtown environments is developed. This approach exploits a 3D geographical database managed by a 3D-GIS and a monovision-based system. The pose estimated by a LRK GPS is ...
Lire la suite >In this paper, an obstacle detection approach for downtown environments is developed. This approach exploits a 3D geographical database managed by a 3D-GIS and a monovision-based system. The pose estimated by a LRK GPS is used to geo-localise the vehicle. After coordinates system conversion, the vehicle is localised in the 3D geographical database. An image processing module is developed to match synchronized images provided by 3D GIS and an on-board camera. Several kinds of obstacles are then detected and tracked by comparison between real images and virtual images. Finally, the distance between the camera and the obstacles is computed, as well as the geo-position of the detected obstacles. Experimental results with real data are presented in the final section.Lire moins >
Lire la suite >In this paper, an obstacle detection approach for downtown environments is developed. This approach exploits a 3D geographical database managed by a 3D-GIS and a monovision-based system. The pose estimated by a LRK GPS is used to geo-localise the vehicle. After coordinates system conversion, the vehicle is localised in the 3D geographical database. An image processing module is developed to match synchronized images provided by 3D GIS and an on-board camera. Several kinds of obstacles are then detected and tracked by comparison between real images and virtual images. Finally, the distance between the camera and the obstacles is computed, as well as the geo-position of the detected obstacles. Experimental results with real data are presented in the final section.Lire moins >
Langue :
Anglais
Comité de lecture :
Oui
Audience :
Internationale
Vulgarisation :
Non
Collections :
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