Computing Thermal Point Clouds by Fusing RGB-D and Infrared Images: From Dense Object Reconstruction to Environment Mapping

Tanhao Zhang, Luyin Hu, Yuxiang Sun, Lu Li, D. Navarro-Alarcon
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引用次数: 2

Abstract

Compared with 2D thermal images, visualizing the temperature of objects with their corresponding 3D surfaces provides a more intuitive way to perceive the environment. In this paper, we present an integrated system for large-scale and real-time 3D thermographic reconstruction through fusion of visible, infrared and depth images. The system is composed of an RGB-D and a thermal camera, whose image measurements are aligned with respect to the same coordinate frame. A thermal direct method based on infrared features is proposed and integrated into state-of-art localization algorithms for generating reliable 3D thermal point clouds. The reported experimental results demonstrate that our approach can be used for 3D reconstruction of small and large scale environments based on dual spectrum 3D information.
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RGB-D与红外图像融合计算热点云:从密集目标重建到环境映射
与二维热图像相比,将物体的温度与其对应的三维表面可视化提供了一种更直观的感知环境的方式。本文提出了一种基于可见光、红外和深度图像融合的大规模实时三维热像重建集成系统。该系统由一个RGB-D和一个热像仪组成,其图像测量相对于同一坐标系对齐。提出了一种基于红外特征的热直接方法,并将其与当前最先进的定位算法相结合,生成可靠的三维热点云。实验结果表明,该方法可用于基于双光谱三维信息的小尺度和大尺度环境的三维重建。
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