as the title says, my question is about a return value given by the calibrateCamera function from OpenCv.
http://docs.opencv.org/modules/calib3d/doc/camera_calibration_a
calibrateCamera
returns the root mean square (RMS) re-projection error, usually it should be between 0.1 and 1.0 pixels in a good calibration.
The calculation is done by projecting the 3D chessboard points (objectPoints
) into the image plane using the final set of calibration parameters (cameraMatrix
, distCoeffs
, rvecs
and tvecs
) and comparing the known position of the corners (imagePoints
).
An RMS error of 1.0 means that, on average, each of these projected points is 1.0 px away from its actual position. The error is not bounded in [0, 1], it can be considered as a distance.