OrthoTrack: Continuous 6-DoF UAV Trajectory Estimation Anchored in Public Orthophotos

• URL: http://arxiv.org/abs/2606.25245v2
• Date: Sun, 28 Jun 2026 11:35:41 GMT
• Title: OrthoTrack: Continuous 6-DoF UAV Trajectory Estimation Anchored in Public Orthophotos
• Abstract summary: We present OrthoTrack, a training-free system that estimates continuous 6-DoF trajectories using only publicly available orthophotos and surface models as a map prior.<n>On MovingDrone and real-world benchmarks, OrthoTrack runs in real time on a single GPU. It outperforms all baselines by a large margin, even those receiving oracle scale and alignment.
• Score: 76.81099730054356
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Continuous 6-DoF pose estimation is essential for autonomous UAV operations. Yet, existing visual odometry and SLAM methods accumulate drift and yield only relative, up-to-scale trajectories. Single-frame geo-localization, in turn, discards temporal continuity and remains too slow for real-time use. We present OrthoTrack, a training-free system that estimates continuous 6-DoF UAV trajectories using only publicly available orthophotos and surface models as a map prior. OrthoTrack matches keyframes against the orthophoto and lifts correspondences to metric 3D via the surface model. It then propagates these map-anchored correspondences to intermediate frames with optical flow, producing absolute, metrically scaled poses at every frame without GPS or post-hoc alignment. We also introduce the MovingDrone Dataset, a large-scale benchmark pairing photorealistic UAV sequences with dense 6-DoF ground truth and co-registered multi-modal geodata including multi-temporal orthophotos. On MovingDrone and real-world benchmarks, OrthoTrack runs in real time on a single GPU. It outperforms all baselines by a large margin, even those receiving oracle scale and alignment. By relying on publicly available geodata, OrthoTrack enables deployment to new regions without site-specific adaptation.

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