Case Study of the 5-point Algorithm for Texturing Existing Building Models from Infrared Image Sequences

Today, thermal inspections of buildings are normally done in recorded single infrared images directly. Thus, no 3d references of found objects and features like i.e. heating pipes or leakages is possible. In computer vision several techniques for the extraction of building surfaces and surface textures from optical images have been developed during the last years. Those algorithms like i.e. 3point matching, surface estimation via homography or the 5-point algorithm introduced by Nistér are specialised for optical images with their strong edges and high resolution. In this paper, the 5-point algorithm introduced by Nistér is adopted for the extraction of textures from infrared images sequences for an already given building model. Special problem caused by the physical behaviour of the infrared spectrum and the technical limitations of the cameras will be discussed including their influence on the usability of the matching algorithm.