Xu Baobei, Ye Zhangyu, Wang Fan, Yang Jiangxin, Cao Yanlong, Tisse Christel-Loic, Li Xin, Cao Yanpeng
Appl Opt. 2019 Apr 20;58(12):3238-3246. doi: 10.1364/AO.58.003238.
The fusion of three-dimensional (3D) geometrical and two-dimensional (2D) thermal information provides a promising method for characterizing temperature distribution of 3D objects, extending infrared imaging from 2D to 3D to support various thermal inspection applications. In this paper, we present an effective on-the-fly calibration approach for accurate alignment of depth and thermal data to facilitate dynamic and fast-speed 3D thermal scanning tasks. For each pair of depth and thermal frames, we estimate their relative pose by minimizing the objective function that measures the temperature consistency between a 2D infrared image and the reference 3D thermographic model. Our proposed frame-to-model mapping scheme can be seamlessly integrated into a generic 3D thermographic reconstruction framework. Through graphics-processing-unit-based acceleration, our method requires less than 10 ms to generate a pair of well-aligned depth and thermal images without hardware synchronization and improves the robustness of the system against significant camera motion.
三维（3D）几何信息与二维（2D）热信息的融合为表征3D物体的温度分布提供了一种很有前景的方法，将红外成像从2D扩展到3D，以支持各种热检测应用。在本文中，我们提出了一种有效的实时校准方法，用于深度数据和热数据的精确对齐，以促进动态和高速的3D热扫描任务。对于每一对深度帧和热帧，我们通过最小化目标函数来估计它们的相对姿态，该目标函数用于测量2D红外图像与参考3D热成像模型之间的温度一致性。我们提出的帧到模型映射方案可以无缝集成到通用的3D热成像重建框架中。通过基于图形处理单元的加速，我们的方法在无需硬件同步的情况下，生成一对对齐良好的深度图像和热图像所需时间不到10毫秒，并提高了系统对相机大幅运动的鲁棒性。
