Infrared simulation of large-scale urban scene through LOD.

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.

Semi-automated infrared simulation on real urban scenes based on multi-view images.

The development of modern infrared applications require simulating thermal representations for targets of interest. However, generating geometric models for simulation has been a laborious, time-consuming work, which greatly limits the practical applications in real-world. In order to reduce the man-in-the-loop requirements, we devise a method that directly and semi-automatically simulates infrared signatures of real urban scenes. From raw meshes generated by multi-view stereo, we automatically produce a simplified watertight model through piecewise-planar 3D reconstruction. Model surface is subdivided into quality mesh elements to attach material attributes. For each element, heat balance equation is solved so as to render the whole scene by synthesizing the radiance distribution in infrared waveband. The credibility and effectiveness of our method are confirmed by comparing simulation results to the measured data in real-world. Our experiments on various types of buildings and large scale scene show that the proposed pipeline simulates meaningful infrared scenes while being robust and scalable.