A camera projects 3D world-points onto the 2D image plane. Traditional cameras have some internal parameter which affect imaging process such as, Image center, Focal length and Lens distortion parameters. In addition to this almost unknown (actually all manufacturers gives their parameters but note that focal lenght will be change when you zoom in or out, and also in order to pyhsical deformations, other parameters might be changed as well) instrinsic parameters, if you want to calculate depth information of scene or 3d scene reconstruction, you have to know positions of cameras according to any reference point. In case of stereo vision application, one camera can be selected as reference point too. That time we need to know rotation and translation of one camera according to another in addition to instrinsic parameters. Generally 1 checkerboard plane is widely used for this aim. Accoding to theoretical background, we need at least 3 different view of one checker board image for all camera. But the more and different image you take, the better accuracy you gain. But if we use 2 or 3 ortogonal checkerboard, we can obtain both instrinsic and extrinsic parameters using only one shot.
In this research, we developed fully automatic 3 orthogonal checkerboards calibration techniques either mono or stereo camera. Actually we calculated the extrinsic parameters according to outher reference point which is intersection point of 3 orthogonal plane.
muhammet balcilar (2019). Stereo-Camera-Calibration-Orthogonal-Planes (https://www.github.com/muhammetbalcilar/Stereo-Camera-Calibration-Orthogonal-Planes), GitHub. Retrieved .