Focus of the paper lies on automated texturing of 3d building modelswith images recorded with infrared (IR) cameras. Therefore, a datafusion of given 3d models and recorded IR image sequences is performed.A relative orientation of the images of the sequence is generatedusing Nister's five-point algorithm and image triplets. This resultsin a point cloud of correspondence points and a relative camera path.The relative oriented image scene is then matched in two steps firstto the recoded GPS camera path and then to the given building withleast squares minimum distance. Textures are extracted for everyimage and its according camera position from all visible surfaces.Because one image does not show complete building facades, the extractedtextures of the images are combined to create complete textures forthe model surfaces. These textures can be used for feature extractionand object recognition for analyzing buildings and assigned 3d coordinatesto found features and objects.     «

Focus of the paper lies on automated texturing of 3d building modelswith images recorded with infrared (IR) cameras. Therefore, a datafusion of given 3d models and recorded IR image sequences is performed.A relative orientation of the images of the sequence is generatedusing Nister's five-point algorithm and image triplets. This resultsin a point cloud of correspondence points and a relative camera path.The relative oriented image scene is then matched in two steps firstto the recoded GPS camera...     »