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A camera calibration procedure intended for a 3D measurement application is presented, paying attention to the various error sources. The error may be measurement noise that is random by nature, but it may also be systematic originating from the calibration target used, geometrical distortions and illumination. In order to obtain good calibration results, the systematic error sources should be eliminated or their effects compensated for. Then, the camera parameters can be determined by fitting the corrected measurements to the camera model which in our case is a combination of a pinhole camera and lens distortion models. We also notice that a more complete camera model is needed to explain all the error components.
Heikkilä et al. (Mon,) studied this question.
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