Paper
9 January 2025 Fast localization method for UAV images in GNSS-denied environments utilizing image sequence relationships
Han Gao, Ying Yu, Wenming Zhang, Yajuan Wang, Li Li, Lei Li, Liang Song, Lei Zhang
Author Affiliations +
Proceedings Volume 13486, Fourth International Conference on Computer Vision, Application, and Algorithm (CVAA 2024); 1348609 (2025) https://doi.org/10.1117/12.3055751
Event: Fourth International Conference on Computer Vision, Application, and Algorithm (CVAA 2024), 2024, Chengdu, China
Abstract
Unmanned aerial vehicle (UAV) image localization can be used in global navigation satellite system (GNSS)-denied environments for UAV self-navigation. This study proposes a fast localization method for UAV images in GNSS-denied environments based on image sequence relationships. First, the LightGlue network extracts features from adjacent UAV images and combines these features with the sequence relationship of the UAV images to perform feature matching within the overlapping range. After eliminating errors, the affine transformation matrix is calculated to realize adjacent image positioning of the UAV. Experiments conducted on multiple image datasets show that the proposed method successfully completes the rapid positioning of UAV images in GNSS-denied environments, with positioning errors less than 0.5 m, indicating potential for practical applications
(2025) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Han Gao, Ying Yu, Wenming Zhang, Yajuan Wang, Li Li, Lei Li, Liang Song, and Lei Zhang "Fast localization method for UAV images in GNSS-denied environments utilizing image sequence relationships", Proc. SPIE 13486, Fourth International Conference on Computer Vision, Application, and Algorithm (CVAA 2024), 1348609 (9 January 2025); https://doi.org/10.1117/12.3055751
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KEYWORDS
Unmanned aerial vehicles

Feature extraction

Satellite navigation systems

Matrices

Error analysis

Image processing

Vegetation

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