Driving in an augmented-city: from fast and automatic large scale environment modeling to on-line 6DOF vehicle localization

Dorra Larnaout 1 Vincent Gay-Bellile 1 Steve Bourgeois 1 Benjamin Labbé 1 Michel Dhome 2
1 LVIC - Laboratoire Vision et Ingénierie des Contenus
DIASI - Département Intelligence Ambiante et Systèmes Interactifs : DRT/LIST/DIASI
Abstract : To provide high quality Augmented Reality service in a car navigation system, accurate 6DoF localization is required. To ensure such accuracy, most of current vision-based solutions rely on an off-line large scale modeling of the environment. Nevertheless, while existing solutions require expensive equipments and/or a prohibitive computation time, we propose in this paper a complete framework that automatically builds an accurate city scale database of landmarks using only a standard camera, a GPS and Geographic Information System (GIS). As illustrated in the experiments, only few minutes are required to model large scale environments. Then, a localization algorithm can use the resulting databases for a high quality Augmented Reality experiences
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Conference papers
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https://hal-cea.archives-ouvertes.fr/cea-01830504
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Submitted on : Thursday, July 5, 2018 - 10:13:15 AM
Last modification on : Friday, April 12, 2019 - 9:56:16 AM

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Dorra Larnaout, Vincent Gay-Bellile, Steve Bourgeois, Benjamin Labbé, Michel Dhome. Driving in an augmented-city: from fast and automatic large scale environment modeling to on-line 6DOF vehicle localization. ACM SIGGRAPH International Conference on Virtual-Reality Continuum and its Applications in Industry, Nov 2013, Hong Kong, China. ⟨10.1145/2534329.2534339⟩. ⟨cea-01830504⟩

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