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Conference papers

Outdoor Obstacles Detection and Localisation with Monovision and 3D Geographical Database

Cindi Cappelle 1 Maan Badaoui 2 François Charpillet Denis Pormski 1
2 STF - Systèmes Tolérants aux Fautes
CRIStAL - Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189
Abstract : 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.
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Conference papers
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Contributor : François Charpillet Connect in order to contact the contributor
Submitted on : Saturday, September 29, 2007 - 3:38:34 PM
Last modification on : Wednesday, March 23, 2022 - 3:51:13 PM


  • HAL Id : inria-00175668, version 1



Cindi Cappelle, Maan Badaoui, François Charpillet, Denis Pormski. Outdoor Obstacles Detection and Localisation with Monovision and 3D Geographical Database. IEEE International Conference on intelligent Transportation Systems, Sep 2007, Seattle, United States. ⟨inria-00175668⟩



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