Very fast road database verification using textured 3D city models obtained from airborne imagery

Abstract

Road databases are known to be an important part of any geodata infrastructure, e.g. as the basis for urban planning or emergency services. Updating road databases for crisis events must be performed quickly and with the highest possible degree of automation. We present a semi-automatic algorithm for road verification using textured 3D city models, starting from aerial or even UAV-images. This algorithm contains two processes, which exchange input and output, but basically run independently from each other. These processes are textured urban terrain reconstruction and road verification. The first process contains a dense photogrammetric reconstruction of 3D geometry of the scene using depth maps. The second process is our core procedure, since it contains various methods for road verification. Each method re-presents a unique road model and a specific strategy, and thus is able to deal with a specific type of roads. Each method is designed to provide two probability distributions, where the first describes the state of a road object (correct, incorrect), and the second describes the state of its underlying road model (applicable, not applicable). Based on the Dempster-Shafer Theory, both distributions are mapped to a single distribution that refers to three states: correct, incorrect, and unknown. With respect to the interaction of both processes, the normalized elevation map and the digital orthophoto generated during 3D reconstruction are the necessary input - together with initial road database entries - for the road verification process. If the entries of the database are too obsolete or not available at all, sensor data evaluation enables classification of the road pixels of the elevation map followed by road map extraction by means of vectorization and filtering of the geometrically and topologically inconsistent objects. Depending on the time issue and availability of a geo-database for buildings, the urban terrain reconstruction procedure has semantic models of buildings, trees, and ground as output. Building s and ground are textured by means of available images. This facilitates the orientation in the model and the interactive verification of the road objects that where initially classified as unknown. The three main modules of the texturing algorithm are: Pose estimation (if the videos are not geo-referenced), occlusion analysis, and texture synthesis

Vectorization of Road Data Extracted From Aerial and Uav Imagery

“…Besides, uncertainties in the georeferencing of both shapefiles and sensor data processing results affects negatively both completeness and correctness. In our previous work (Bulatov et al, 2014b), the road networks from free geographic data, sensor data evaluation results, as well as superposition of both, were analyzed for the dataset Bonnland first by the statistical reasoning approach based on Dempster and Shafer theory (Ziems, 2014) and finally by interactive analysis of both incorrect and unknown segments, see (Bulatov et al, 2014b), using the textured urban terrain model. Through the automatic verification step, there were many unknown segments (since they exhibit too high curvature or are too short compared to standard GIS roads).…”