Traditional non-coplanar calibration methods such as Tsai’s method have many problems, such as insufficient calibration accuracy, inconvenient operation, inaccurate models, etc. This paper proposes a new high-precision non-coplanar calibration method that aims to solve these problems. Like Tsai’s method, the proposed calibration method utilizes a one-dimensional displacement stage and a two-dimensional plane target to generate a virtual 3D feature point sequence. As an improvement, an affine coordinate correction model is applied to ensure the accuracy and orthogonality of the obtained virtual 3D coordinates. A novel and accurate camera calibration model is further established. Compared with Tsai’s model, which uses a radial alignment constraint and ignores the orthonormal constraint of the rotation matrix, the proposed calibration model fully considers the degrees of freedom of the camera’s parameters to be calibrated, as well as the lens’s nonlinear distortion parameters. More accurate analytical solutions of intrinsic and extrinsic parameters can be obtained with the proposed calibration model. Finally, a novel high-precision non-coplanar calibration method is proposed based on the proposed calibration model. The reprojection experiment proves that the calibration accuracy of this calibration method is better than that of Tsai’s and Zhang’s calibration methods under the same calibration conditions. As a supplement, a novel binocular camera system extrinsic parameter calibration method with known intrinsic parameters is proposed. With accurate intrinsic and extrinsic parameters, the binocular camera system’s relative measurement accuracy could be within 1/10 000. Overall, this method can be used in experimental and industrial applications that require high-precision calibration parameters.

Traditional non-coplanar calibration methods, represented by Tsai’s method, are difficult to apply in multi-camera-based stereo vision measurements because of insufficient calibration accuracy, inconvenient operation, etc. Based on projective theory and matrix transformation theory, a novel mathematical model is established to characterize the transformation from targets’ 3D affine coordinates to cameras’ image coordinates. Then, novel non-coplanar calibration methods for both monocular and binocular camera systems are proposed in this paper. To further improve the stability and accuracy of calibration methods, a novel circular feature points extraction method based on region Otsu algorithm and radial section scanning method is proposed to precisely extract the circular feature points. Experiments verify that our novel calibration methods are easy to operate, and have better accuracy than several classical methods, including Tsai’s and Zhang’s methods. Intrinsic and extrinsic parameters of multi-camera-systems can be calibrated simultaneously by our methods. Our novel circular feature points extraction algorithm is stable, and with high precision can effectively improve calibration accuracy for coplanar and non-coplanar methods. Real stereo measurement experiments demonstrate that the proposed calibration method and feature extraction method have high accuracy and stability, and can further serve for complicated shape and deformation measurements, for instance, stereo-DIC measurements, etc.