User-Aided Geo-location of Untagged Desert Imagery
| Autor: | Andrew Zhai, Eric Tzeng, Avideh Zakhor, Matthew Clements, Raphael J. L. Townshend |
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| Rok vydání: | 2016 |
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| Zdroj: | Large-Scale Visual Geo-Localization ISBN: 9783319257792 Large-Scale Visual Geo-Localization |
| Popis: | We propose a system for user-aided visual localization of desert imagery without the use of any metadata such as GPS readings, camera focal length, or field-of-view. The system makes use only of publicly available datasets—in particular, digital elevation models (DEMs)—to rapidly and accurately locate photographs in nonurban environments such as deserts. Our system generates synthetic skyline views from a DEM and extracts stable concavity-based features from these skylines to form a database. To localize queries, a user manually traces the skyline on an input photograph. The skyline is automatically refined based on this estimate, and the same concavity-based features are extracted. We then apply a variety of geometrically constrained matching techniques to efficiently and accurately match the query skyline to a database skyline, thereby localizing the query image. We evaluate our system using a test set of 44 ground-truthed images over a \(\text {10,000}\,\mathrm{km}^{2}\) region of interest in a desert and show that in many cases, queries can be localized with precision as fine as \(100\,\mathrm{m}^{2}\). |
| Databáze: | OpenAIRE |
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