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Lane detection and scene interpretation by particle filter in airport areas

Abstract : Lane detection has been widely studied in the literature. However, it is most of the time applied to the automotive field, either for Advanced Driver-Assistance Systems (ADAS) or autonomous driving. Few works concern aeronautics, i.e. pilot assistance for taxiway navigation in airports. Now aircraft manufacturers are interested by new functionalities proposed to pilots in future cockpits, or even for autonomous navigation of aircrafts in airports. In this paper, we propose a scene interpretation module using the detection of lines and beacons from images acquired from the camera mounted in the vertical fin. Lane detection is based on particle filtering and polygonal approximation, performed on a top view computed from a transformation of the original image. For now, this algorithm is tested on simulated images created by a product of the OKTAL-SE company.
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Contributor : Claire Meymandi-Nejad <>
Submitted on : Thursday, July 11, 2019 - 3:07:49 PM
Last modification on : Thursday, June 10, 2021 - 3:04:05 AM


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  • HAL Id : hal-02180537, version 1


Claire Meymandi-Nejad, Salwa Kaddaoui, Michel Devy, Ariane Herbulot. Lane detection and scene interpretation by particle filter in airport areas. 14th International Conference on Computer Vision Theory and Applications (VISAPP 2019), Feb 2019, Prague, Czech Republic. ⟨hal-02180537⟩



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