Thermal imaging with drone
Most methods use 2D thermal images because they are easily obtainable. However, the proposed procedure for 3D model reconstruction in this paper can provide helpful support in making interpretation and evaluation of thermal data more automatic, faster and objective. Contrary to other methods, thermal imaging can work in environments without ambient light. It can penetrate obscurants like smoke, haze, and fog. The paper will address the challenge of 3D reconstruction from images of thermal infrared (TIR). It seeks to demonstrate that commercial computer vision software may be used to orient the sequence of TIR images from a drone and produce 3D point cloud without having to acquire any GNSS/IN information about altitude and position of images or the parameters of the camera calibration. The paper proposes a procedure which is based on “Iterative Closest Point algorithm (ICP)” to come up with a model which combines the geometric precision and also high resolution of RGB with thermal information from TIR images. Keywords: Photogrammetry, Unmanned Aerial Vehicles, Computer Vision, Thermal Infrared Images List of Acronyms UAV Unmanned Aerial Vehicle TIR Thermal Infrared RGB Red, Green and Blue CPUCentral Processing Unit CUDACompute Unified Device Architecture GCP Ground Control Points GPU Graphic Processing Unit MSAC M-estimator Sample Consensus GNSS Global Navigation Satellite System SFM Structure from motion IntroductionThermal imaging is a way of improving the visibility of an object in a constrained…
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