摄像机自标定算法通常是非线性的，为了得到线性的方法，提出了一种在RANSAC框架下由4对图像对应点线性标定摄像机并对场景进行鲁棒性欧氏重建的方法。当摄像机作两组平移运动时，若在两组平移运动之间摄像机具有不同的姿态，则从4对图像对应点可以线性地重建场景的欧氏几何。模拟实验和真实图像实验均证明了本文方法的可行性。

Usually, camera self-calibration is nonlinear. A linear camera calibration technique based on four point correspondences is proposed in this paper in order to obtain a linear method, and a robust Euclidean reconstruction under the random sample consensus (RANSAC) algorithms is computed from the images. The main results are: Assuming the camera undergoes two sets of translations, of which the corresponding rotation axes of camera are not parallel, then Euclidean geometry of a scene can be reconstructed linearly from four point correspondences. Experimental results on synthetic and real images have validated the proposed linear technique.