OrthoTrack: Continuous 6-DoF UAV Trajectory Estimation Anchored in Public Orthophotos
Quick Answer
OrthoTrack is a training-free system for continuous 6-DoF UAV trajectory estimation using public orthophotos, achieving real-time performance on a single GPU.
Quick Take
It significantly outperforms existing methods, providing absolute poses without GPS, and introduces the MovingDrone Dataset for benchmarking.
Key Points
- OrthoTrack uses public orthophotos and surface models for 6-DoF pose estimation.
- It propagates map-anchored correspondences using optical flow for real-time performance.
- The system outperforms all baselines, even those with oracle scale and alignment.
- MovingDrone Dataset pairs UAV sequences with dense 6-DoF ground truth data.
- Deployment to new regions requires no site-specific adaptation.
Paper Resources
📖 Reader Mode
~2 min readAbstract: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.
| Comments: | ECCV 2026 - Project page: this http URL |
| Subjects: | Computer Vision and Pattern Recognition (cs.CV) |
| Cite as: | arXiv:2606.25245 [cs.CV] |
| (or arXiv:2606.25245v1 [cs.CV] for this version) | |
| https://doi.org/10.48550/arXiv.2606.25245 arXiv-issued DOI via DataCite (pending registration) |
Submission history
From: Oussema Dhaouadi [view email]
[v1]
Wed, 24 Jun 2026 00:05:01 UTC (22,958 KB)
— Originally published at arxiv.org
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