Abstract: Camera calibration plays a critical role in the field of computer vision. Most of the camera calibration methods assume the pinhole camera model and require well-focused images to ensure precise estimation of the intrinsic and extrinsic camera parameters. However, they are often impaired by lens systems with limited depth of field(DoF). In this paper, we propose a weighted camera calibration method that takes the defocus amount of control points into account. Under the assumption of a thin-lens camera model, blur estimation is performed for each individual control point on the calibration target with a checkerboard pattern. The defocus amount of individual control points participates in the calibration procedure in a weighted form to improve the accuracy of the results. No additional device or special calibration target is needed. Experiments were conducted using both synthetic and real images, and the results showed that the proposed method achieves higher accuracy than the conventional methods.