TY - GEN

T1 - Very fast road database verification using textured 3D city models obtained from airborne imagery

AU - Bulatov, Dimitri

AU - Ziems, Marcel

AU - Rottensteiner, Franz

AU - Pohl, Melanie

PY - 2014/10/23

Y1 - 2014/10/23

N2 - 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 represents 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.

AB - 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 represents 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.

KW - Building reconstruction

KW - Dempster-shafer theory

KW - Road database

KW - Texturing

KW - Urban terrain

KW - Verification

UR - http://www.scopus.com/inward/record.url?scp=84923064730&partnerID=8YFLogxK

U2 - 10.1117/12.2066823

DO - 10.1117/12.2066823

M3 - Conference contribution

AN - SCOPUS:84923064730

T3 - Proceedings of SPIE - The International Society for Optical Engineering

BT - Image and Signal Processing for Remote Sensing XX

A2 - Benediktsson, Jon Atli

A2 - Bovolo, Francesca

A2 - Bruzzone, Lorenzo

PB - SPIE

T2 - Image and Signal Processing for Remote Sensing XX

Y2 - 22 September 2014 through 24 September 2014

ER -