camera_calibration_and_stereo_vision []

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Marker tracking using a pair of cameras is a common task, however setting up and calibrating the cameras can be challenging
In the SoRo Adhesives project, we designed a stereo-vision setup that can be adapted to other projects
The scripts used are based on the work of Temuge Batpurev which is hosted on [[https://github.com/TemugeB/python_stereo_camera_calibrate?tab=readme-ov-file|GitHub]

Camera calibration relies on acquiring images of a checkerboard using two cameras (see image below)
This file can be used to generate checkerboards for calibration
Checkerboard images are used to obtain the intrinsic matrices and distortion coefficients of each camera individually
The camera calibration process also outputs a value related to the quality of the calibration (RMSE) which should be less than 0.30
Note that both camera frames must have the same dimensions for stereo calibration