The geolocalization of aerial images is important for extracting geospatial information (e.g. the position of buildings, streets, cars, etc.) and for creating maps. The standard is to use an expensive aerial imaging system equipped with an accurate GPS and IMU and/or do laborious Ground Control Point measurements. In this paper we present a novel method to recognize the geolocation of aerial images automatically without any GPS or IMU. We extract road segments in the image sequence by detecting and tracking cars. We search in a database created from a road network map for the best matches between the road database and the extracted road segments. Geometric hashing is used to retrieve a shortlist of matches. The matches in the shortlist are ranked by a verification process. The highest scoring match gives the location and orientation of the images. We show in the experiments that our method can correctly geolocalize the aerial images in various scenes: e.g. urban, suburban, rural with motorway. Beside the current images only the road map is needed over the search area. We can search an area of 22500 km 2 containing 32000 km of streets within minutes on a single cpu.
In REF , they extract road segments in image sequences and search in a database created from a road network map for the best matches between the road database and the extracted road segments.
Aerial image sequence geolocalization with road traffic as invariant feature
Image Vis. Comput.
Image Vis. Comput.
Mathematics Computer Science