Improved outdoor augmented reality through "Globalization"

Despite the major interest in live tracking and mapping (e.g., SLAM), the field of augmented reality has yet to truly make use of the rich data provided from large-scale reconstructions generated by structure from motion. This dissertation focuses on extensible tracking and mapping for large-scale reconstructions that enables SfM and SLAM to operate cooperatively to mutually enhance the performance. We describe a multi-user, collaborative augmented reality system that will collectively extend and enhance reconstructions of urban environments at city-scales. Contrary to current outdoor augmented reality systems, this system is capable of continuous tracking through areas previously modeled as well as new, undiscovered areas. Further, we describe a new process called globalization that propagates new visual information back to the global model. Globalization allows for continuous updating of the 3D models with visual data from live users, providing data to fill coverage gaps that are common in 3D reconstructions and to provide the most current view of an environment as it changes over time. The proposed research is a crucial step toward enabling users to augment urban environments with location-specific information at any location in the world for a truly global augmented reality.