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ICF-Loc: An Infrared-Based Coarse-to-Fine Approach for UAV Visual Geolocation under GPS-Denied Environments | IEEE Conference Publication | IEEE Xplore

ICF-Loc: An Infrared-Based Coarse-to-Fine Approach for UAV Visual Geolocation under GPS-Denied Environments


Abstract:

Visual geolocation plays a crucial role when GPS is unavailable in the Unmanned Aerial Vehicles (UAVs). Many methods rely on visible light cameras, which may not perform ...Show More

Abstract:

Visual geolocation plays a crucial role when GPS is unavailable in the Unmanned Aerial Vehicles (UAVs). Many methods rely on visible light cameras, which may not perform well in low-light or foggy conditions. To address this issue, we propose an advanced UAV visual geolocation method called ICF-Loc, which utilizes infrared images in a coarse-to-fine approach. ICF-Loc consists of two stages: a retrieval-based coarse localization stage and a matching-based fine localization stage. The goal of the coarse localization stage is to identify the satellite image that is most similar to the UAV’s infrared image. To bridge the distribution gap between the visible and infrared domains, we propose a feature transfer module. In the fine localization stage, the UAV’s infrared image is matched with the satellite image obtained during coarse localization to estimate the UAV’s position and orientation accurately. We have designed a cross-modal image matching method based on the Fourier transform for precise estimation. The experimental results demonstrate the effectiveness of our proposed approach on both synthetic and real-world datasets.
Date of Conference: 15-19 July 2024
Date Added to IEEE Xplore: 30 September 2024
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Conference Location: Niagara Falls, ON, Canada

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