摄像机自标定是三维重建技术的基本问题，得到许多学者的大力研究.为了简化摄像机自标定过程，一般假设摄像机内参数中的倾斜因子为零，然后对主点和焦距进行自标定.但在摄像机模型为完全的射影模型时，即当倾斜因子 (Skew Factor)值较大时，则使用上述假设得到的自标定参数误差较大，有时甚至无法得到结果.为了对倾斜因子值较大的摄像机进行准确标定，提出了一种当摄像机的倾斜因子已知但不为零时的摄像机自标定方法，试验结果证明该方法可以得到比较准确的摄像机内参数，并可使得后续的三维重建得到较好的结果.

Camera self-calibration is a fundamental problem in 3D reconstruction from un-calibrated image sequences and has been investigated by many researchers in recent years. In order to simplify the camera self-calibration process, the skew factor of the camera is usually assumed to be zero to get a group of linear equations where initial values of the camera's intrinsic parameters can be estimated, then a non-linear algorithm initialized with these values can be used to optimize the self-calibration result. However, when the camera is a complete perspective model, i.e. when the skew factor of the camera is not zero, the error of the self-calibration with the above assumption will be very large and sometimes the self-calibration algorithms will fail to get any result at all. In order to overcome the above problem, this paper addresses a self-calibration algorithm that can successfully compute the intrinsic parameters when the skew factor of the camera is not zero but known. Experiment results of synthetic data as well as real image sequences show that this algorithm can estimate the camera's intrinsic parameters precisely and make the successive 3D reconstruction more easily.