This paper addresses the problem of 3D building reconstruction from thermal infrared (TIR) images. We show that a commercial Computer Vision software can be used to automatically orient sequences of TIR images taken from an Unmanned Aerial Vehicle (UAV) and to generate 3D point clouds, without requiring any GNSS/INS data about position and attitude of the images nor camera calibration parameters. Moreover, we propose a procedure based on Iterative Closest Point (ICP) algorithm to create a model that combines high resolution and geometric accuracy of RGB images with the thermal information deriving from TIR images. The process can be carried out entirely by the aforesaid software in a simple and efficient way.
REF show that a commercial computer vision software can be used to automatically orient sequences of TIR images taken from an UAV and to generate 3D point clouds, without requiring any Global Navigation Satellite System (GNSS) and Inertial Navigation System (INS) data about position and attitude of the images.
PHOTOGRAMMETRIC 3D BUILDING RECONSTRUCTION FROM THERMAL IMAGES
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Computer Science