The invention belongs to the field of computer vision and the field of point cloud processing, and relates to a method for synchronously realizing human face three-dimensional point cloud feature point positioning and human face segmentation, which comprises the following steps: S1, point cloud initialization: inputting human face point cloud data; S2, projection: projecting the point cloud information with the texture onto a 2D image; S3, 2D feature point positioning: positioning face feature points on the projected 2D image; S4S4, solving 3D feature points: solving the feature points of theface three-dimensional point cloud according to the corresponding relationship; S5, segmentation: cutting the face point cloud data by using the feature point information; S6, trimming: removing pointcloud outliers; S7, iteration: returning to S2 to resolve the point cloud feature points, and performing iteration until the point cloud feature points are stable; and S8, outputting: outputting theclipped face point cloud and the clipped face 3D feature points. According to the method, the 3D human face feature points are synchronously positioned, the human face point cloud is cut, the two processes are mutually promoted, the human face point cloud feature points can be solved with high precision, and the method is simple, convenient, feasible, efficient and practical.