基于球几何特征的摄像机内参分步标定方法

在摄像机标定过程中，球形靶标对图像数量、拍摄角度要求小，能够适应遮挡环境，在使用中具有明显优势.在分析球投影模型几何性质的基础上，提出一种利用球靶标分步标定摄像机内部参数的方法.该方法通过拍摄一幅包含空间中2个不同位置球体的图像，得到图像中的2条投影二次曲线；利用2条投影二次曲线的对称轴和公切线计算球心投影点，通过投影二次曲线的对称轴确定图像主点坐标，根据球心投影点和图像主点的位置关系求解归一化焦距；利用整体优化算法得到内参标定结果.仿真数据实验分析了引入测量误差的主要因素，实物标定结果与平面方格靶标方法相比误差在5%之内，重复测量结果稳定.

Camera calibration from geometric feature of spheres

Camera calibration with spheres has little demand on image number, camera shooting angle and high adaptivity to occlusion, which has an obvious advantage in applications. A novel camera calibration method was proposed based on geometric feature of sphere projection model. This algorithm used two projection conics of spheres and solved the intrinsic parameters of the camera. The projection conics were obtained from image of two spheres at different positions. The symmetry axis and common tangent of the projection conics were used to solve the principal point and the projections of sphere centers. Then normalized focal length was computed based on geometric relationship of the principal point and projection of sphere center. Finally intrinsic parameters were obtained using optimization algorithm. Simulation data experiments analyze the main error factors and real data results show that the proposed method is reliable and the error is less than 5% comparing with planar target method.