This paper presents a metric global localization in the urban environment only with a monocular camera and the Google Street View database. We fully leverage the abundant sources from the Street View and benefits from its topo-metric structure to build a coarse-to-fine positioning, namely a topological place recognition process and then a metric pose estimation by local bundle adjustment. Our method is tested on a 3 km urban environment and demonstrates both sub-meter accuracy and robustness to viewpoint changes, illumination and occlusion. To our knowledge, this is the first work that studies the global urban localization simply with a single camera and Street View.
@article{arxiv.1605.05157,
title = {Monocular Urban Localization using Street View},
author = {Li Yu and Cyril Joly and Guillaume Bresson and Fabien Moutarde},
journal= {arXiv preprint arXiv:1605.05157},
year = {2016}
}