Metadata-free Georegistration of Ground and Airborne Imagery
This addresses the need for aligning 3D models in real-world coordinates for applications like mapping and reconstruction, though it appears incremental as it builds on existing 3D modeling techniques.
The paper tackles the problem of georegistering ground and airborne imagery without metadata by leveraging satellite imagery and neural radiance fields, resulting in successful georegistration across various sites.
Heterogeneous collections of ground and airborne imagery can readily be used to create high-quality 3D models and novel viewpoint renderings of the observed scene. Standard photogrammetry pipelines generate models in arbitrary coordinate systems, which is problematic for applications that require georegistered models. Even for applications that do not require georegistered models, georegistration is useful as a mechanism for aligning multiple disconnected models generated from non-overlapping data. The proposed method leverages satellite imagery, an associated digital surface model (DSM), and the novel view generation capabilities of modern 3D modeling techniques (e.g. neural radiance fields) to provide a robust method for georegistering airborne imagery, and a related technique for registering ground-based imagery to models created from airborne imagery. Experiments demonstrate successful georegistration of airborne and ground-based photogrammetric models across a variety of distinct sites. The proposed method does not require use of any metadata other than a satellite-based reference product and therefore has general applicability.