The shape analysis and shape transformation of the laser-scanning point cloud model depend on the curve skeleton. We proposed a fast and automatic method to obtain the curve skeleton of laser-scanning point cloud to transform the shape of the model and reduce the time consumption caused by manually binding the skeleton. In this method， the initial skeleton point is defined as the midpoint of the nearest correlation point with symmetrical normal in the point cloud. The final skeleton point is obtained by iterating the initial skeleton point to a balance position. Then the principal component analysis method is used to search for the combination of skeleton points that meet the requirements of direction consistency， and the breadth-first search method is used to merge the growing different skeleton branches. Finally， each branch is smoothed and connected by the Laplace smoothing method， a complete skeleton line is obtained and the curve skeleton is used in the task of model shape transformation. The proposed method is compared with the L₁-Medial Skeleton， the Mass-driven Topology-aware Curve Skeleton method and other methods， and the original scanned point cloud is used as the test data to verify the effectiveness， robustness， and efficiency. The extraction efficiency of the proposed model is improved to the level that it takes 0.764 s to process the point cloud composed of 8 077 points， and it takes 4.356 s to process a point cloud with 33 041 points. The curve skeleton of laser scanned point cloud extracted is applied to the task of shape transformation of point cloud， which shows the practicability of this method.