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The recent availability of large-scale geo-tagged images on social and photo-sharing websites has spurred a growing interest in developing automatic methods for image geolocalization. The challenges of visual analysis and geolocalization of large-scale imagery arise in a variety of real-world applications. Consumers of imagery may be interested in determining when and where an image/video was taken, who is in the image, what the different objects in the depicted scene are, and how they are related to each other. Local government agencies may be interested in using large-scale imagery to automatically obtain and index useful geographic and geological features and their distributions in a region of interest. Similarly, local businesses may utilize content statistics to target their marketing based on the 'where', 'what', and 'when' that may automatically be extracted during visual analysis and geolocalization of large-scale imagery. Research on visual analysis and geolocalization of large-scale imagery can greatly benefit by bringing together researchers from areas of computer vision, computer graphics, photogrammetry, computational optimization, geographic information systems, and other related fields, which is the focus of this book.
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