An Improved Two-Stage Camera Calibration Method Based on Particle Swarm Optimization

According to the calibration of binocular vision, an improved two-stage camera calibration method involved with multi-distortion coefficients is introduced in this paper. At the first stage, the 3D points' coordinate are calculated by the imitated direct linear transformation (DLT) triangulation based on distortion compensation. And at the second stage, particle swarm optimization (PSO) is selected to determine two cameras' parameters. In this way the parameters of the two cameras can be tuned simultaneously. In order to assist estimating the performance of the proposed method, a new cost function is designed. Simulation and experiment are made under the same calibration data sets. The performance of PSO used to tune the parameters is also compared to that of GA. The experiment results show that the strategy of taking the 3D reconstruction errors as object function is feasible and PSO is the best choice for camera parameters' optimization.