Flexible and accurate camera calibration using grid spherical images

Abstract

For important camera calibration in the field of computer vision, a new target form, namely, a grid spherical target (GST) that is different from the spherical target, is proposed. The GST has advantages of spherical and checkerboard targets because of the grid on the sphere. And the latitude and longitude circles and the intersection points between latitude and longitude circles on the GST are used to calibrate the camera. Firstly, the Image of Absolute Conic should be obtained using the elliptic curves of latitude and longitude circles on the GST in the images. After obtaining the initial intrinsic and extrinsic parameters of the camera using the Image of Absolute Conic, optimum solutions of the intrinsic and extrinsic parameters are solved through nonlinear optimization by using the latitude circles and the intersection points of the latitude and longitude lines. Finally, the effectiveness of the GST-based method is proven in simulation and physical experiments.