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 recordedsingle infrared images directly. Thus, no 3d references of found objects and features like i.e. heating pipes or leakages ispossible. In computer vision several techniques for the extractionof building surfaces and surface textures from optical images have beendeveloped during the last years. Those algorithms like i.e. 3-point matching, surface estimation via homography or the 5-point algorithmintroduced by Nistér are specialised for optical images with their strong edges and high resolution. In this paper, the 5-pointalgorithm introduced by Nistér is adopted for the extraction of textures from infrared images sequences for an already given buildingmodel. Special problem caused by the physical behaviour of the infrared spectrum and the technical limitations of the cameraswill be discussed including their influence on the usability of thematching algorithm.     «

Today, thermal inspections of buildings are normally done in recordedsingle infrared images directly. Thus, no 3d references of found objects and features like i.e. heating pipes or leakages ispossible. In computer vision several techniques for the extractionof building surfaces and surface textures from optical images have beendeveloped during the last years. Those algorithms like i.e. 3-point matching, surface estimation via homography or the 5-point algorithmintroduced by Nistér are specialis...     »