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Monocular Urban Localization using Street View


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.
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hal-01425639 , version 1 (03-01-2017)


  • HAL Id : hal-01425639 , version 1


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⟩
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