首先，基于经典RANSAC算法检测三维点云中的球面区域。检测时在点云中

First, based on the classic spherical region RANSAC algorithm detects a three-dimensional point cloud. <br>Randomly selected detection point cloud iteratively sample points, while using an analytical method to solve the spherical parameters, and finally the least squares method is calculated using the correction parameters according to the spherical inner spherical current optimal parameter set of points corresponding to the point cloud, to reduce the error.

First, the spherical area in the three-dimensional point cloud is detected based on the classic RANSAC algorithm.<br>When detecting, the sample points are selected at random in the point cloud, the spherical parameters are solved by parsing method, and the spherical parameters are calculated using the least square method to correct the spherical parameters according to the inner point set corresponding to the current optimal spherical parameters in the point cloud, in order to reduce the error.

Firstly, based on the classical RANSAC algorithm, the spherical region in 3D point cloud is detected.<br>At the same time, the spherical parameters are solved by the analytic method. Finally, the spherical parameters are corrected by the least square method according to the inner point set corresponding to the current optimal spherical parameters in the point cloud to reduce the error.<br>