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