Abstract
The growing use of infrared (IR) imaging systems places increasing demands for simulating infrared images of real scenes. Utilizing images captured from unmanned aerial vehicles (UAV), we propose a semi-automatic pipeline to generate large-scale IR urban scenes in the form of levels of detail (LODs). It significantly reduces the cost of labor and time while providing detailed IR structures. Starting from the surface meshes generated by multi-view stereo (MVS) systems, we produce watertight LODs via semantic segmentation and structure-aware approximation. For each LOD, we divide the surfaces into triangle facets of specific scales. For each facet, one material attribute is attached, and the heat balance equations are solved to obtain the temperature. Three strategies are proposed to accelerate the thermal distribution calculation. Finally, by synthesizing the radiance distribution, the whole IR scenes are generated and rendered. Experiments on real urban scenes show that the proposed pipeline could effectively simulate IR scenes of large-scale urban scenes.
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