Mobile thermal mapping for matching of infrared images with 3D building models and 3D point clouds

Two workflows for mobile thermal mapping including geometric camera calibration, automatic image orientation, 3D reconstruction and extraction of textures of building façades from thermal IR image sequences are introduced. In the first method, a coregistration of a terrestrial image sequence is done with a given 3D building model with the 3D building model being included in the image sequence orientation directly. Homologue image points are tracked through the sequence and checked whether they are on the 3D model façade. This is done to remove outliers and to refine the image sequence orientation and 3D reconstruction process as additional constraint in the bundle adjustment. The second method is used to match a high resoluted RGB-image based 3D point cloud and a TIR-image based 3D point cloud to assign thermal intensities to the dense RGB point cloud. The matching is done based on given pre-orientation of the two-point clouds performing Iterative Closest Point to minimise the distance of the two-point clouds. The corrected orientation is transferred to the orientation parameters of the TIR-images. The final image orientations are used to extract thermal textures for the 3D building model. Both methods are evaluated on their geometric accuracy using experimental image sequences.     «

Two workflows for mobile thermal mapping including geometric camera calibration, automatic image orientation, 3D reconstruction and extraction of textures of building façades from thermal IR image sequences are introduced. In the first method, a coregistration of a terrestrial image sequence is done with a given 3D building model with the 3D building model being included in the image sequence orientation directly. Homologue image points are tracked through the sequence and checked whether they a...     »