We extend recent automated computer vision algorithms to reconstruct the global three-dimensional structures for photos and videos shot at fixed points in outdoor city environments. Mosaics of digital stills and embedded videos are georegistered by matching a few of their 2D features with 3D counterparts in aerial ladar imagery. Once image planes are aligned with world maps, abstract urban knowledge can propagate from the latter into the former. We project geotagged annotations from a 3D map into a 2D video stream and demonstrate their tracking buildings and streets in a clip with significant panning motion. We also present an interactive tool which enables users to select city features of interest in video frames and retrieve their geocoordinates and ranges. Implications of this work for future augmented reality systems based upon mobile smart phones are discussed.
['Peter Cho', 'Soonmin Bae', 'Frédo Durand']
Image-based querying of urban photos and videos