In order to improve the accuracy of feature point extraction and reduce the error in the reconstructed 3D space in camera calibration, we propose a full-threshold segmentation and multi-constraint binocular fisheye camera calibration algorithm in this paper. To address the problems of large noise in edge regions and insufficient fitting accuracy of feature points in traditional calibration, firstly, based on the unified fisheye imaging model, a Gaussian function is used to iteratively fit the grayscale histogram and a global full-threshold segmentation method is applied to accurately extract circular calibration feature points, thereby achieving high-precision feature identification in distorted images. In addition, multi-constraint optimization function that integrates vertical and collinear constraints is proposed as a supplement to distance and epipolar constraints. It fully exploits 3D information in the inverse-projection stage of spatial point reconstruction, simultaneously considers the overall 3D spatial structure and local geometric relationships of the reconstructed points. In implementation, a circular calibration board combined with a global-threshold-based ellipse boundary detection strategy is adopted, and the multi-constraint objective function is iteratively solved using the Levenberg-Marquardt algorithm, thereby improving the convergence and stability of parameter estimation. Experiments are conducted on a binocular fisheye system, where multiple calibration tests are performed and evaluation metrics including distance error, epipolar error, vertical error, and collinear error were used. The experimental results show that the proposed method attains high accuracy in feature-point detection and parameter optimization: the mean reprojection error (MRE) is reduced by 30.85% compared with traditional methods, the 3D spatial error is reduced by about 45%, and the average error on the test images is below 0.3%, which verifies significant improvements in both accuracy and robustness. This study provides a reliable parameter foundation for high-precision calibration of binocular fisheye vision systems.