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Journal articles

Fast and automatic city-scale environment modelling using hard and/or weak constrained bundle adjustments

Dorra Larnaout 1 Vincent Gay-Bellile 1 Steve Bourgeois 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 6 degrees of freedom (DoF) localization is required. To ensure such accuracy, most current vision-based solutions rely on an off-line large-scale modelling of the environment. Nevertheless, while existing solutions to model the environment require expensive equipments and/or a prohibitive computation time, we propose in this paper a complete framework that automatically builds an accurate large-scale database of landmarks using only a standard camera, a low-cost global positioning system (GPS) and a geographic information system (GIS). As illustrated in the experiments, only few minutes are required to model large-scale environments. The resulting databases can then be used by an on-line localization algorithm to ensure high-quality augmented reality experiences.
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Submitted on : Thursday, July 5, 2018 - 10:20:38 AM
Last modification on : Thursday, February 17, 2022 - 10:08:05 AM



Dorra Larnaout, Vincent Gay-Bellile, Steve Bourgeois, Michel Dhome. Fast and automatic city-scale environment modelling using hard and/or weak constrained bundle adjustments. Machine Vision and Applications, Springer Verlag, 2016, 27 (6), pp.943 - 962. ⟨10.1007/s00138-016-0766-6⟩. ⟨cea-01830512⟩



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