多视点三维数据合并中的定标球球心算法

利用每个数据点的k-近邻点计算其法向量，并以扫描区域中心点的法向量为基准，使所有点的法向量指向球心；然后根据扫描仪的测量精度计算误差范围，以扫描区域中心点法向量的延长端点为中心提取出球面数据点；最后以球面数据点法向量延长端的质心为该定标球的球心．大量真实数据实验表明，文中算法具有较高的精度和较好的稳定性．

Algorithm for Finding Registration Sphere Center in Merging Multiple-View 3D Point Clouds

From the measured sphere data, the normal of each point is calculated according to its k-nearest neighbors, and every normal vector is adjusted to the same orientation as that of the scanning frame center, i.e. pointing towards the sphere center. Then, all points on the sphere surface are extracted with the criterion that their diametrically opposite points are located on the sphere, centered at the normal vector of scanning frame center with the radius taking into account the scanner's measurement error. Finally, the centroid of diametrically opposite points located on the lengthened normal of all extracted points determines the center of registration sphere. Experiments on real data show the high accuracy and good stability of this algorithm.