Towards Bundle Adjustment with GIS Constraints for Online Geo-Localization of a Vehicle in Urban Center

Vehicle geo-localization using a single camera is a challenging issue promoted by several limitations that GPS incurs in dense urban area. While most of the existing solutions rely on viewpoint recognition techniques, the combination of Structure from Motion algorithm and the geometric information provided by Geographic Information System (GIS) has emerged as a promising alternative. In this system paper, we introduce a monocular SLAM process that exploits both "Digital Elevation Model" layer (DEM) and "3D buildings model" layer of a GIS to reach an accurate and robust geo-localization. Our solution relies on a constrained bundle adjustment that exploits the DEM to correct the camera trajectory while the 3D buildings model is used to constrain the reconstructed 3D points cloud. ore over, our solution is designed to achieve an on-line and real-time (i.e. about 30 Hz) localization while most of the state of the art solutions are off-line. In addition to evaluations on different synthetic and real large scale sequences, an Augmented Reality application is realized proving these statements.