Optimally Weighted Linear Algorithm for Camera Calibration with 1D Objects

This paper proposes an optimally weighted linear algorithm to further improve the accuracy of linear algorithm for camera calibration with 1D objects.A new estimator for the relative depths are proposed by optimally weighting their constraint equations only once,and it is shown that noniterative optimal weighting can ensure similar accuracy to iterative weighting as well as reduced computational cost;The constraint equations on the image of the absolute conic are also optimally weighted only once,where the optimal weights are appropriately simplified to further reduce the computational cost.The experimental results demonstrate that the calibration accuracy of the proposed algorithm is higher than that of the existing weighted linear algorithm,and is comparable to the accuracy of the bundle adjustment algorithm.