基于描述符的模式的多 RGB-D 相机外部标定新方法。

A Novel Method for Extrinsic Calibration of Multiple RGB-D Cameras Using Descriptor-Based Patterns.

机构信息

School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200444, China.

School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, China.

出版信息

Sensors (Basel). 2019 Jan 16;19(2):349. doi: 10.3390/s19020349.

DOI:10.3390/s19020349

PMID:30654568

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6359178/

Abstract

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.

摘要

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。