Long-distance spatial position measurement based on multi-camera system

Camera calibration is the first and the most important step of spatial position measurement. Aiming at improving the measurement precision over a large field of view and long distance, the internal and external parameters of the camera need to be calibrated accurately. Therefore, a simple and accurate calibration method is proposed to solve the problem that a small calibration board cannot appear in the field of view of multiple cameras at the same time. We calibrate the internal and external parameters of camera separately. For the internal parameters, we calculate it using analytical solution estimation method after collecting calibration plate images for feature point detection. For the external parameters, we accurately obtain the relative positions of the cameras with the help of the total station, and then unify the pose relationship of each camera to the same coordinate system through rigid body transformation to obtain the parameters. Then, the maximum likelihood method is used to optimize the estimation of both internal and external parameters to improve the calibration accuracy. Finally, the three-dimensional coordinates of target can be obtained by triangulation. The experimental results show that this method meets requirement of calibration accuracy, and the error of the 3D spatial position of the target is in the centimeter level.