Accurate Stereo Vision System Calibration withChromatic Concentric Fringe Patterns

2021 ◽  
Author(s):  
Shiyong An ◽  
Hongyu Yang ◽  
Pei Zhou ◽  
Wenfan Xiao ◽  
Jiangping Zhu ◽  
...  
2018 ◽  
Vol 161 ◽  
pp. 03020 ◽  
Author(s):  
Ramil Safin ◽  
Roman Lavrenov ◽  
Subir Kumar Saha ◽  
Evgeni Magid

Calibration is essential for any robot vision system for achieving high accuracy in deriving objects metric information. One of typical requirements for a stereo vison system in order to obtain better calibration results is to guarantee that both cameras keep the same vertical level. However, cameras may be displaced due to severe conditions of a robot operating or some other circumstances. This paper presents our experimental approach to the problem of a mobile robot stereo vision system calibration under a hardware imperfection. In our experiments, we used crawler-type mobile robot «Servosila Engineer». Stereo system cameras of the robot were displaced relative to each other, causing loss of surrounding environment information. We implemented and verified checkerboard and circle grid based calibration methods. The two methods comparison demonstrated that a circle grid based calibration should be preferred over a classical checkerboard calibration approach.


Author(s):  
Paweł Rotter ◽  
Witold Byrski ◽  
Michał Dajda ◽  
Grzegorz Łojek

AbstractIn the double-plane method for stereo vision system calibration, the correspondence between screen coordinates and location in 3D space is calculated based on four plane-to-plane transformations; there are two planes of the calibration pattern and two cameras. The method is intuitive, and easy to implement, but, the main disadvantage is ill-conditioning for some spatial locations. In this paper we propose a method which exploits the third plane which physically does not belong to the calibration pattern, but can be calculated from the set of reference points. Our algorithm uses a combination of three calibration planes, with weights which depend on screen coordinates of the point of interest; a pair of planes which could cause numerical errors receives small weights and have practically no influence on the final results. We analyse errors, and their distribution in 3D space, for the basic and the improved algorithm. Experiments demonstrate high accuracy and reliability of our method compared to the basic version; root mean square error and maximum error, are reduced by factors of 4 and 20 respectively.


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