Research On Camera Calibration Without Control Points In The View

In photogrammetry, in order to raise measurement precision, we should ensure that its internal and external parameters remain unchanged. So the camera is not allowed to move when the calibration is complete. But it will be difficult to work when the target we measured was at sea or in the air, because there will be no control points can be used in the camera’s field of view.In order to solve the camera calibration problem without control points in the visual field, this paper proposes two solutions ideas: One way is coordinate system conversion calibration method based on the total station; the other way is the calibration method based on linear laser imaging cameras.The first method is an indirect calibration method, this paper to the total station horizontal rotation axis and the vertical axis of rotation coordinate system to create a total station coordinates system, which is independent of the world coordinate system. And the total station coordinates system should maintain the three-dimensional structural information of the object unchanged during the motion. Above all, we combine the camera with the total station tightly, and calibrate the internal and external parameters in the total station coordinates system. Then we transferred it to the world coordinate system of the place where we do the experiment. In this way, it can be used for subsequent measurements.The second method is direct calibration method through a straight line played by laser. The basic idea is make a laser light imaging in the camera’s field of view, and extracted it’s parameters with total station. According to the parameters of the laser line and the line on the camera, we can do the pose estimation.The main work is as follows:1) We designed a video measurement system based on the total station associated with the camera fixed on a rigid platform, and proposed a calibration method based on the total station coordinate system conversion, and illustrate the feasibility of the method through theoretical analysis and experimental verification2) We extended the points-based projection model to the lines-based projection model and derive a linear projection model based pose estimation method too.3) We devoted a general discussion to the radial distortion model. It corrected the linear distortion, and solved out a set of data corresponding to the radius first. Then fit the distortion model and observed treatment effect with the fitting out distortion model.4) We analyzed the far-distance measurement with the result calibrated in close-distance, and made some changes on the basis of the previous model for pinhole.