Research on multi-camera calibration and point cloud correction method based on three-dimensional calibration object

Abstract The single camera measurement system can't obtain all the surface information of the object limited by the field of view, thus it can't achieve complete measurement of the object. Multi-camera system can overcome this difficulty. But it is difficult to unify the coordinate system of distinct cameras. In order to solve this problem, a global calibration method of multi-camera system is proposed. A three-dimensional cube calibration object is designed. Every camera is only calibrated on one surface of the cube calibration object. Because different surfaces of the cube calibration object are in a unified world coordinate, the coordinates of the feature points on different surfaces are naturally in the unified world coordinate system. Thus global calibration can be completed by calibrating multiple cameras at the same time. In addition, to minimize the error of calibration, a correction method is proposed. The correction parameters are obtained by the deviation between the world coordinates and the reconstructed coordinates of the feature points on calibration object. The parameters are applied to the measurement to improve the accuracy of the whole point cloud. Experiments are carried out on a multi-camera measurement system, and the results show that the method proposed in this paper is effective and feasible.