一种基于4对图像对应点的欧氏重建方法

A Euclidean Reconstruction Method Based on Four Point Correspondences

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。

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.