Uneven Image Point Distribution in Camera Pre- Calibration and its Effects on 3D Reconstruction Errors

In camera pre-calibration, images of a calibration object are commonly used to determine the internal geometry of a camera. The calibration imaging is often optimized to have the calibration object cover as large image area as possible. This is likely to yield a larger concentration of measured image points near the center of the image sensor. In this report, the hypothesis is investigated that this non-uniform image point distribution results in a sub-optimal calibration. An area-based reweighting scheme is suggested to improve the calibration. Additionally, the effect of a choice between a 2D and a 3D calibration object is investigated. A simulation study was performed where both a standard and area-weighted pre-calibration scheme was used in a parallel and a convergent scene. The estimated uncertainty and true errors were computed and compared to the first order predictions and results of perfect calibrations. The area-based calibration showed no reduction in estimation errors. Furthermore, the 3D calibration object did not give a noticeable improvement. However, for the standard and area-based calibrations, the true errors surpassed the estimated uncertainties by up to 26 and 58 percent, respectively.