[1] Besl P J. Amethod for registration of 3D shapes［J］. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1992, 14(3): 239-256.

[2] 钟莹, 张蒙. 基于改进ICP算法的点云自动配准技术［J］. 控制工程, 2014, 21(1): 37-40.

    Zhong Ying, Zhang Meng. Automatic registration technology of point cloud based on improved ICP algorithm［J］. Control Engineering of China, 2014, 21(1): 37-40.

[3] Yang J, Li H, Campbell D, et al. Go-ICP:a globally optimal solution to 3D ICP point-set registration［J］. IEEE Transactions on Pattern Analysis & Machine Intelligence, 2016, 38(11): 2241-2254.

[4] 曾繁轩, 李亮, 刁鑫鹏. 基于曲率特征的迭代最近点算法配准研究［J］. 激光与光电子学进展, 2017, 54(1): 011003.

    Zeng Fanxuan, Li Liang, Diao Xinpeng. Iterative closest point algorithm registration based on curvature features［J］. Laser & Optoelectronics Progress, 2017, 54(1): 011003.

[5] 陈茂霖, 卢维欣, 万幼川, 等. 无附加信息的地面激光点云自动拼接方法［J］. 中国激光, 2016, 43(4): 0414003.

    Chen Maolin, Lu Weixin, Wan Youchuan, et al. Automatic registration of terrestrial point clouds without additional information［J］. Chinese J Lasers, 2016, 43(4): 0414003.

[6] 陆军, 彭仲涛, 夏桂华. 点云多法向量邻域特征配准算法［J］. 光电子·激光, 2015(4): 780-787.

    Lu Jun, Peng Zhongtao, Xia Guihua. Point cloud registration algorithm based on neighborhood features of multi-scale normal vectors［J］. Journal of Optoelectronics·Laser, 2015(4): 780-787.

[7] He F, Ayman H. A closed-form solution for coarse registration of point clouds using linear features［J］. Journal of Surveying Engineering, 2016, 142(3): 04016006.

[8] Rusu R B, Blodow N, Beetz M. Fast point feature histograms (FPFH) for 3D registration［C］. IEEE, 2009: 3212-3217.

[9] Rusu R B, Blodow N, Marton Z C, et al. Aligning point cloud views using persistent feature histograms［C］. IEEE, 2008: 3384-3391.

[10] Tombari F, Salti S, Stefano L D. Unique signatures of histograms for local surface description［J］. Lecture Notes in Computer Science, 2010, 6313: 356-369.

[11] Bastian S, Rusu R B, Konolige K, et al. NARF: 3D range image features for object recognition［C］. Workshop on Defining and Solving Realistic Perception Problems in Personal Robotics at the IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS), 2010: 44.

[12] Zhang Y, Yu H Y. 3D point cloud registration based on the assistant camera and Harris-SIFT［C］. International Workshop on Pattern Recognition, 2016, 10011: 100110U.

[13] 马骊溟, 徐毅, 李泽湘. 基于高斯曲率极值点的散乱点云数据特征点提取［J］. 系统仿真学报, 2008, 20(9): 2341-2344.

    Ma Liming, Xu Yi, Li Zexiang. Extracting feature points for scattered points based on Gauss curvature extreme point［J］. Journal of System Simulation, 2008, 20(9): 2341-2344.

[14] 王丽辉, 袁保宗. 三维散乱点云模型的特征点检测［J］. 信号处理, 2011, 27(6): 932-938.

    Wang Lihui, Yuan Baozong. Feature point detection for 3D scattered point cloud model［J］. Signal Processing, 2011,27(6): 932-938.

[15] 陈西江, 章光, 花向红. 于法向量夹角信息熵的点云简化算法［J］. 中国激光, 2015, 42(8): 0814003.

    Chen Xijiang, Zhang Guang, Hua Xianghong. Point cloud simplification based on the information entropy of normal vector angle［J］. Chinese J Lasers, 2015, 42(8): 0814003.