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SKYLINE2GPS: Localization in Urban Canyons using Omni-Skylines

Srikumar Ramalingam 1 Sofien Bouaziz 1 Peter Sturm 2 Matthew Brand 1 
2 PERCEPTION - Interpretation and Modelling of Images and Videos
Inria Grenoble - Rhône-Alpes, LJK - Laboratoire Jean Kuntzmann, Grenoble INP - Institut polytechnique de Grenoble - Grenoble Institute of Technology
Abstract : This paper investigates the problem of geo-localization in GPS challenged urban canyons using only skylines. Our proposed solution takes a sequence of upward facing omnidirectional images and coarse 3D models of cities to compute the geo-trajectory. The camera is oriented upwards to capture images of the immediate skyline, which is generally unique and serves as a fingerprint for a specific location in a city. Our goal is to estimate global position by matching skylines extracted from omni-directional images to skyline segments from coarse 3D city models. Under day-time and clear sky conditions, we propose a sky-segmentation algorithm using graph cuts for estimating the geo-location. In cases where the skyline gets affected by partial fog, night-time and occlusions from trees, we propose a shortest path algorithm that computes the location without prior sky detection. We show compelling experimental results for hundreds of images taken in New York, Boston and Tokyo under various weather and lighting conditions (daytime, foggy dawn and night-time).
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Submitted on : Wednesday, October 6, 2010 - 7:16:44 PM
Last modification on : Friday, November 18, 2022 - 9:24:45 AM

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Srikumar Ramalingam, Sofien Bouaziz, Peter Sturm, Matthew Brand. SKYLINE2GPS: Localization in Urban Canyons using Omni-Skylines. IROS 2010 - IEEE/RSJ International Conference on Intelligent Robots and Systems, Oct 2010, Taipei, Taiwan. pp.3816-3823, ⟨10.1109/IROS.2010.5649105⟩. ⟨inria-00523997⟩



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