Introduction To Large-Scale Visual Geo-Localization

Despite recent advances in computer vision and large-scale indexing techniques, automatic geo-localization of images and videos remains a challenging task. The majority of existing computer vision solutions for geo-localization are limited to highly-visited urban regions for which a significant amount of geo-tagged imagery is available, and therefore, do not scale well to large and ordinary geospatial regions. In this chapter, we provide an overview of the major research themes in visual geo-localization, investigate the challenges, and point to problem areas that will benefit from common synthesis of perspectives from these research themes. In particular, we discuss how the availability of web-scale geo-referenced data affects visual geo-localization, what role semantic information plays in this problem, and howprecise localization can be achieved using large-scale textured (RGB) and untextured (non-RGB) 3D models. We also introduce a few real-world applications which became feasible as a result of the capability of estimating an image's geo-location. We conclude this chapter by providing an overview of the emerging trends in visual geo-localization and a summary of the rest of the chapters of the book.