Open AccessResearch on Calibration Method of Multi-camera System without Overlapping Fields of View Based on SLAM
Author(s) -
Mingyue Feng,
Panpan Jiang,
Yibo Liu,
Jingshu Wang
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1544/1/012047
Subject(s) - camera auto calibration , computer vision , camera resectioning , artificial intelligence , computer science , calibration , process (computing) , simultaneous localization and mapping , basis (linear algebra) , camera matrix , pinhole camera model , robot , mathematics , mobile robot , statistics , geometry , operating system
The basis of multi-camera system measurement is the calibration of the multi-camera system. Although multi-camera system calibration has achieved certain results, there are still problems such as tedious calibration process and high calibration cost. In this paper, we propose a practical calibration method for multi-camera systems without overlapping fields of view. Firstly, a global 3D model of the scene is reconstructed using Simultaneous Localization and Mapping (SLAM). Then, each camera is calibrated using the 2D-3D correspondence between the images acquired by the multi-camera system and the 3D model. Finally, the external parameters of the multi-camera system are calibrated. In the process of using SLAM to build the model, the graph optimization is used to improve the accuracy of the modeling, and the accuracy of the calibration depends on the accuracy of the modeling. After several experiments, the experimental results show that the method is feasible.