Overhead-based image and video geo-localization framework

This paper presents a geo-localization framework of street-level outdoor images using multiple sources of overhead reference imagery including LIDAR, Digital Elevation Maps and Multi-Spectral Land Cover/Use imagery. We describe five different matchers and an adaptive linear fusion process which combines individual matchers' probability maps into a single map. These matchers exploit mountain elevation profiles, rendered camera views, landmarks, landuse classes and building heights. We successfully validated our framework on 100 queries with geographic truth in two world regions (each of 10, 000km(2)) in the USA.