Camera pose refinement by matching uncertain 3D building models with thermal infrared image sequences for high quality texture extraction

Thermal infrared (TIR) images are often used to picture damaged and weak spots in the insulation of the building hull, which is widely used in thermal inspections of buildings. Such inspection in large-scale areas can be carried out by combining TIR imagery and 3D building models. This combination can be achieved via texture mapping. Automation of texture mapping avoids time consuming imaging and manually analyzing each face independently. It also provides a spatial reference for façade structures extracted in the thermal textures. In order to capture all faces, including the roofs, façades, and façades in the inner courtyard, an oblique looking camera mounted on a flying platform is used. Direct geo-referencing is usually not sufficient for precise texture extraction. In addition, 3D building models have also uncertain geometry. In this paper, therefore, methodology for co-registration of uncertain 3D building models with airborne oblique view images is presented. For this purpose, a line-based model-to-image matching is developed, in which the uncertainties of the 3D building model, as well as of the image features are considered. Matched linear features are used for the refinement of the exterior orientation parameters of the camera in order to ensure optimal co-registration. Moreover, this study investigates whether line tracking through the image sequence supports the matching. The accuracy of the extraction and the quality of the textures are assessed. For this purpose, appropriate quality measures are developed. The tests showed good results on co-registration, particularly in cases where tracking between the neighboring frames had been applied.