Registration of Spherical Panoramic Images with Cadastral 3D Models

The availability of geolocated panoramic images of urban environments has been increasing in the recent past thanks to services like Google Street View, Microsoft Street Side, and Navteq. Despite the fact that their primary application is in street navigation, these images can be used, along with cadastral information, for city planning, real-estate evaluation and tracking of changes in an urban environment. The geolocation information, provided with these images, is however not accurate enough for such applications: this inaccuracy can be observed in both the position and orientation of the camera, due to noise introduced during the acquisition. We propose a method to refine the calibration of these images leveraging cadastral 3D information, typically available in urban scenarios. We evaluated the algorithm on a city scale dataset, spanning commercial and residential areas, as well as the countryside.