Abstract : 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 topolog-ical 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.
https://hal.archives-ouvertes.fr/hal-01425639
Contributor : Fabien Moutarde
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Submitted on : Tuesday, January 3, 2017 - 4:57:00 PM
Last modification on : Monday, November 12, 2018 - 10:54:20 AM
Document(s) archivé(s) le : Tuesday, April 4, 2017 - 2:44:02 PM
Li Yu, Cyril Joly, Guillaume Bresson, Fabien Moutarde. Monocular Urban Localization using Street View. 14th International Conference on Control, Automation, Robotics and Vision (ICARCV'2016), Nov 2016, Phuket, Thailand. ⟨hal-01425639⟩
