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

Continuous 6-DoF pose estimation is essential for au-tonomous UAV operations. Yet, existing visual odometry and SLAMmethods accumulate drift and yield only relative, up-to-scale trajecto-ries. Single-frame geo-localization, in turn, discards temporal continu-ity and remains too slow for real-time use. We present OrthoTrack, atraining-free system that estimates continuous 6-DoF UAV trajectoriesusing only publicly available orthophotos and surface models as a mapprior. OrthoTrack matches keyframes against the orthophoto and liftscorrespondences to metric 3D via the surface model. It then propagatesthese map-anchored correspondences to intermediate frames with opticalflow, producing absolute, metrically scaled poses at every frame with-out GPS or post-hoc alignment. We also introduce the MovingDroneDataset, a large-scale benchmark pairing photorealistic UAV sequenceswith dense 6-DoF ground truth and co-registered multi-modal geodataincluding multi-temporal orthophotos. On MovingDrone and real-worldbenchmarks, OrthoTrack runs in real time on a single GPU. It outper-forms all baselines by a large margin, even those receiving oracle scaleand alignment. By relying on publicly available geodata, OrthoTrackenables deployment to new regions without site-specific adaptation.