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Proceedings Paper

Performance evaluation of image-based location recognition approaches based on large-scale UAV imagery
Author(s): Nikolas Hesse; Christoph Bodensteiner; Michael Arens
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Paper Abstract

Recognizing the location where an image was taken, solely based on visual content, is an important problem in computer vision, robotics and remote sensing. This paper evaluates the performance of standard approaches for location recognition when applied to large-scale aerial imagery in both electro-optical (EO) and infrared (IR) domains. We present guidelines towards optimizing the performance and explore how well a standard location recognition system is suited to handle IR data. We show on three datasets that the performance of the system strongly increases if SIFT descriptors computed on Hessian-Affine regions are used instead of SURF features. Applications are widespread and include vision-based navigation, precise object geo-referencing or mapping.

Paper Details

Date Published: 13 October 2014
PDF: 6 pages
Proc. SPIE 9250, Electro-Optical Remote Sensing, Photonic Technologies, and Applications VIII; and Military Applications in Hyperspectral Imaging and High Spatial Resolution Sensing II, 92500N (13 October 2014); doi: 10.1117/12.2067179
Show Author Affiliations
Nikolas Hesse, Fraunhofer-Institut für Optronik, Systemtechnik und Bildauswertung (Germany)
Christoph Bodensteiner, Fraunhofer-Institut für Optronik, Systemtechnik und Bildauswertung (Germany)
Michael Arens, Fraunhofer-Institut für Optronik, Systemtechnik und Bildauswertung (Germany)


Published in SPIE Proceedings Vol. 9250:
Electro-Optical Remote Sensing, Photonic Technologies, and Applications VIII; and Military Applications in Hyperspectral Imaging and High Spatial Resolution Sensing II
Gary Kamerman; Gary J. Bishop; Ainsley Killey; Ove Steinvall; John D. Gonglewski, Editor(s)

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