The widespread availability of high resolution aerial imagery covering wide geographical areas is spurring a revolution in large scale visual data analytics. Our research in this area focuses particularly on how analytics for wide-area motion imagery (WAMI) can be enhanced by incorporating information from geographical information systems (GIS) enabled by rapid pixel-accurate registration of vector roadmaps to the WAMI frames and exploitation of this information in vehicle tracking and 3D georegistration. The work particularly highlights how image processing and computer vision applications are a fertile ground for incorporating machine learning and data science methodologies.
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