基于直线的射影不变性和极线约束标定摄像机参数

提出一种用图像对标定摄像机参数的新方法。传统自标定方法需要先由图像特征计算基础矩阵，该方法则是从图像中提取一组未知长度和长度比的平行直线，以图像中心坐标为主点初值，利用直线的射影不变性先求得摄像机焦距、旋转矩阵和平移向量的初值；再由图像对固有的极线约束来优化摄像机的参数，从而得到高精度的主点、焦距、旋转矩阵和平移向量。使用该方法对图像目标进行三维重建，仿真实验表明：该方法对场景要求较少，原理简单，方法易行，标定摄像机参数精度较高。

Self-calibration of camera parameters by image pair based on projective invariance of lines

A new approach to calibrate camera parameters by image pair is presented. With this method, the parameters of a camera is calculated by using the invariance of lines under the projective transformation, different from previous methods which estimate the fundamental matrix by the image characteristics. Two parallel lines on each of the image pair were extracted. The focus and the extrinsic parameters were solved according to the projective invariance of parallel lines with the center of the image taken as initialization of the principal point. Based on the polar constraint, the nonlinear optimization was employed to compute the precise parameters of the camera. The algorithm needs less information of the scene and accurate self-calibration is easily realized. The recovery of 3D scene structure can be accomplished with the new algorithm. Experimental results on the synthetic and real images demonstrate the feasibility of this algorithm.