Improved particle swarm optimization algorithm based nonlinear calibration of camera

Camera calibration has been a very important problem for 3D objects measurement technique, because it will have a impact on the measurement accuracy. Plane-based camera calibration is usually used in camera calibration. In order to solve the nonlinear optimization problem during the process of plane-based camera calibration, a new method is proposed in this paper. Firstly, the intrinsic and extrinsic parameters of linear camera model are obtained by direct linear transformation (DLT). Then, the intrinsic parameters are used as the initial values of the Particle Swarm Optimization (PSO) algorithm to calculate the optimal values of intrinsic, in addition, the camera nonlinear model is used to obtain the extrinsic parameters. Finally the accurate parameters values are given. An example is given to show that the method can improve the calibration precision obviously compared with existing method.