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Erschienen in: Autonomous Robots 7/2020

14.07.2020

Geolocalization with aerial image sequence for UAVs

verfasst von: Yongfei Li, Hao He, Dongfang Yang, Shicheng Wang, Meng Zhang

Erschienen in: Autonomous Robots | Ausgabe 7/2020

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Abstract

The estimation of geolocation for aerial images is significant for tasks like map creating, or automatic navigation for unmanned aerial vehicles (UAVs). We propose a novel geolocalization method for the UAVs using only aerial images and reference road map. The corresponding road maps of the aerial images are firstly merged into a whole mosaic image using our newly-designed aerial image mosaicking algorithm, where the relative homography transformations between road images are firstly estimated using keypoints tracking in RGB aerial images, and then further refined with registration between detected roads. The geolocalization of the aerial mosaic image is then taken as the problem of registering observed roads in the aerial images to the reference road map under the homography transformation. The registration problem is solved with our fast search algorithm based on a novel projective-invariant feature, which consists of two road intersections augmented with their tangents. Experiments demonstrate that the proposed method can localize the aerial image sequence over an area larger than 1000 km\(^2\) within a few seconds.

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Metadaten
Titel
Geolocalization with aerial image sequence for UAVs
verfasst von
Yongfei Li
Hao He
Dongfang Yang
Shicheng Wang
Meng Zhang
Publikationsdatum
14.07.2020
Verlag
Springer US
Erschienen in
Autonomous Robots / Ausgabe 7/2020
Print ISSN: 0929-5593
Elektronische ISSN: 1573-7527
DOI
https://doi.org/10.1007/s10514-020-09927-8

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