School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200444, China.
School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, China.
Sensors (Basel). 2019 Jan 16;19(2):349. doi: 10.3390/s19020349.
This paper presents a novel method to estimate the relative poses between RGB-D cameras with minimal overlapping fields of view. This calibration problem is relevant to applications such as indoor 3D mapping and robot navigation that can benefit from a wider field of view using multiple RGB-D cameras. The proposed approach relies on descriptor-based patterns to provide well-matched 2D keypoints in the case of a minimal overlapping field of view between cameras. Integrating the matched 2D keypoints with corresponding depth values, a set of 3D matched keypoints are constructed to calibrate multiple RGB-D cameras. Experiments validated the accuracy and efficiency of the proposed calibration approach.
本文提出了一种新的方法，用于估计具有最小重叠视场的 RGB-D 相机之间的相对姿态。这种标定问题与室内 3D 地图绘制和机器人导航等应用相关，这些应用可以通过使用多个 RGB-D 相机获得更宽的视场。所提出的方法依赖于基于描述符的模式，以便在相机之间具有最小重叠视场的情况下提供良好匹配的 2D 关键点。将匹配的 2D 关键点与相应的深度值集成在一起，可以构建一组 3D 匹配关键点，以对多个 RGB-D 相机进行标定。实验验证了所提出的标定方法的准确性和效率。
