We show how to use simple 2.5D maps of buildings and recent advances in image segmentation and machine learning to geo-localize an input image of an urban scene: We first extract the façades of the buildings and their edges from the image, and then look for the orientation and location that align a 3D rendering of the map with these segments. We discuss how to use a 3D tracking system to acquire the data required for training the segmentation method, the segmentation itself, and how we use the segmentations to evaluate the quality of the alignment.
|Title of host publication||Proceedings of the Joint Urban Remote Sensing Event (JURSE)|
|Publication status||Published - 2017|
|Event||Joint Urban Remote Sensing Event 2017 - Dubai, United Arab Emirates|
Duration: 6 Mar 2017 → 8 Mar 2017
|Conference||Joint Urban Remote Sensing Event 2017|
|Abbreviated title||JURSE 2017|
|Country/Territory||United Arab Emirates|
|Period||6/03/17 → 8/03/17|
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Best Paper Award at JURSE 2017
Armagan, Anil (Recipient), Hirzer, Martin (Recipient) & Lepetit, Vincent (Recipient), 8 Mar 2017
Prize: Prizes / Medals / Awards