Image-Based Large-Scale Geo-localization in Mountainous Regions.

Saurer, O., Baatz, G., Köser, K., Ladicky, L. and Pollefeys, M. (2016) Image-Based Large-Scale Geo-localization in Mountainous Regions. In: Large-Scale Visual Geo-Localization. , ed. by Zamir, A., Hakeem, A., Van Gool, L., Shah, M. and Szeliski, R.. Advances in Computer Vision and Pattern Recognition, 3 . Springer International Publishing, Cham, pp. 205-223. ISBN 978-3-319-25779-2 DOI 10.1007/978-3-319-25781-5_11.

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Abstract

Given a picture taken somewhere in the world, automatic geo-localization of such an image is an extremely useful task especially for historical and forensic sciences, documentation purposes, organization of the world’s photographs and intelligence applications. While tremendous progress has been made over the last years in visual location recognition within a single city, localization in natural environments is much more difficult, since vegetation, illumination, seasonal changes make appearance-only approaches impractical. In this chapter, we target mountainous terrain and use digital elevation models to extract representations for fast visual database lookup. We propose an automated approach for very large-scale visual localization that can efficiently exploit visual information (contours) and geometric constraints (consistent orientation) at the same time. We validate the system at the scale of Switzerland (40000km2) using over 1000 landscape query images with ground truth GPS position.

Document Type: Book chapter
Keywords: Image-Based, Large-Scale, Geo-localization, Mountainous Regions, Switzerland
Research affiliation: OceanRep > GEOMAR > FB2 Marine Biogeochemistry > FB2-MG Marine Geosystems > DeepSea Monitoring
OceanRep > GEOMAR > FB2 Marine Biogeochemistry > FB2-MG Marine Geosystems
DOI etc.: 10.1007/978-3-319-25781-5_11
Date Deposited: 13 Dec 2016 08:25
Last Modified: 23 Sep 2019 19:41
URI: http://oceanrep.geomar.de/id/eprint/35192

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