3D exploitation of 2D ground-level & aerial imagery

Working with 2.3K+ digital images shot around MIT, we form a SIFT graph which imposes an initial topological ordering upon the quasi-random set of input urban photos. We next employ iterative bundle adjustment algorithms developed by Snavely et al to recover the MIT photos' geometrical structure. After georegistering the 2.3K+ images to an aerial ladar map, we plot recovered camera geolocations on a Google Map and conduct virtual tours through the 3D field of 2D urban photos. Similar computer vision techniques are applied to video footage collected over a rural scene by an aerial glider. 1.5K video frames are reconstructed and georegistered via the UAV's GPS track. We demonstrate how several difficult aerial video exploitation problems become tractable when a geometry-based analysis approach is adopted.