Geospatial Management and Utilization of Large-Scale Urban Visual Reconstructions

Abstract

In this work we describe our approach to efficiently create, handle and organize large-scale Structure-from-Motion reconstructions of urban environments. For acquiring vast amounts of data, we use a Point Grey Ladybug 3 omni directional camera and a custom backpack system with a differential GPS sensor. Sparse point cloud reconstructions are generated and aligned with respect to the world in an offline process. Finally, all the data is stored in a geospatial database. We incorporate additional data from multiple crowd-sourced databases, such as maps from OpenStreetMap or images from Flickr or Instagram. We discuss how our system could be used in potential application scenarios from the area of Augmented Reality.