DSM-Free UAV Visual Localization via Latent-Depth Variable Projection and Structure-Adaptive Coupling
Visual localization enables unmanned aerial vehicles (UAVs) to maintain absolute positioning in GNSS-denied environments. A common approach matches UAV images with geo-tagged orthographic maps and estimates camera pose using Perspective-n-Point (PnP) with elevations from Digital Surface Models (DSMs). However, accurate and up-to-date DSMs are often unavailable in practice. Orthographic-perspective geometry (OPG) enables DSM-free localization in scenes with varying elevations, yet existing methods typically estimate pose indirectly through intermediate matrix estimation and decomposition. To address this limitation, we propose Latent-Depth Variable Projection (LDVP), which treats the unkno...
| Authors | Yibin Ye, Xichao Teng, Shuo Chen et al. |
|---|---|
| Primary category | cs.CV |
| Published | 10 October 2026 |
| Last updated at source | 10 October 2026 |
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