How to interpret actual Camera Intrinsics/Principal Points results?
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Hi everyone,
I have a question regarding the results of the MATLAB calibration, particularly the principal points in the camera intrinsics matrix.
I ran a set of 22 images with checkerboard through the MATLAB calibrator and got the Intrinsics parameter below. The image sizes are [2048, 3072]. Correct me if I am wrong, does the results below means that the principal axis/optical centre is so far off the centre of the camera sensor, almost at the boarder of the sensor (bold text)? For comparison, I ran the same set of images through OpenCV calibrations, and got very different results for Intrinsics -- The principal point is off centre in the other corner, but more central. Should I trust the MATLAB results? and if not, what should I do?
MATLAB:
Intrinsics
----------
Focal length (pixels): [45400.9202 +/- 561.3442 45378.6716 +/- 555.5501]
Principal point (pixels):[ 1221.2838 +/- 89.0373 151.5073 +/- 151.2339]
Radial distortion: [ 0.6755 +/- 0.1693 -111.5748 +/- 46.9582 ]
OpenCV:
[ 43799.33953, 0.0000, 2073.60946;
0.0000, 43818.89133, 1603.30986;
0.0000, 0.0000, 1.0000]
Thank you very much!
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Answers (1)
Matt J
on 27 Jan 2023
The uncertainty values look kind of large to me. I wonder if your 22 images are diverse enough.
8 Comments
Matt J
on 2 Feb 2023
The best suggestion I can make for now is that you use follow this example,
to detect and verify the checkerboard points yourself. Once it is verified that the corners are being well-detected, we can discuss how to proceed.
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