Auto 3-d complex building detection from satellite imagery

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The extraction of 3D geometric building information from high-resolution electro-optical imagery is becominga key element in numerous geospatial applications. Indeed, producing 3D urban models is a requirement for avariety of applications, such as spatial analysis of urban design, military simulation, and site monitoring of aparticular geographic location. Almost all operational approaches developed over the years for 3D buildingreconstruction are semi-automated ones, where a skilled human operator is involved in the 3D geometrymodeling of building instances, a time-consuming process. Further, such approaches usually require stereoimage pairs, image sequences, or laser scanning of a specific geographic location to extract the 3D models fromthe imagery. Finally, with current techniques, the 3D geometric modeling phase may be characterized by theextraction of 3D building models with low accuracy levels.This research aims for a fully automated 3D Structure Detection that copes with imaging of arbitrary viewpointvariations, clutter, and occlusion using monocular panchromatic air/spaceborne images. The system will bedesigned to deal with complications arising from complex shapes and interference due to the close proximity ofurban city buildings. There are numerous applications for a consistent reliable system of extracting geometricinformation from remotely sensed imagery. Some of these include: urban planning and airport hazard analysis,civilian emergency mitigation, natural disaster management (flooding, earthquakes, and landslides), militarysurveillance (active engagement of force, counter terrorism and peace keeping measures, and for statisticalgeographic localization (such as health, crime, and past natural disasters).