[1] Shui W Y, Zhou M Q, Deng Q Q et al. 266: 573. e1-, 573, e12(2016).

[2] Liang R H, Chen C, Pan Z G et al. New algorithm for 3D facial model reconstruction and its application in VR[J]. Proceedings of SPIE, 4756, 79-86(2003).

[3] Lee Y, Terzopoulos D, Walters K. Realistic modeling for facial animation[C]//Proceedings of the 22nd Annual Conference on Computer Graphics and Interactive Techniques, August 6-11, 1995, Los Angeles, CA, USA., 55-62(1995).

[4] Shui W Y, Zhou M Q, Wu Z K et al. An approach of craniofacial reconstruction based on registration[J]. Journal of Computer-Aided Design & Computer Graphics, 23, 607-614(2011).

[5] Zhao F Q, Zhou M Q, Geng G H et al. Rigid blocks matching method based on contour curves and feature regions[J]. IET Computer Vision, 12, 76-85(2018).

[6] Izumiya S, Nabarro A C. Sacramento A D J. Pseudo-spherical normal Darboux images of curves on a timelike surface in three dimensional Lorentz-Minkowski space[J]. Journal of Geometry and Physics, 97, 105-118(2015).

[7] Huang J H, Wang Z, Gao J M et al. High-precision registration of point clouds based on sphere feature constraints[J]. Sensors, 17, 72(2016).

[8] Jiang J, Cheng J, Chen X L. Registration for 3-D point cloud using angular-invariant feature[J]. Neurocomputing, 72, 3839-3844(2009).

[9] Cao Z C, Ma F L, Fu Y L et al. A scale invariant interest point detector in Gabor based energy space[J]. Acta Automatica Sinica, 40, 2356-2363(2014).

[10] Geng N, Ma F F, Yang H J et al. Neighboring constraint-based pairwise point cloud registration algorithm[J]. Multimedia Tools and Applications, 75, 16763-16780(2016).

[11] Nguyen V T, Tran T T, Cao V T et al. 3D point cloud registration based on the vector field representation. [C]//2013 2nd IAPR Asian Conference on Pattern Recognition, November 5-8, 2013, Naha, Japan. New York: IEEE(2013).

[12] Besl P J. McKay N D. A method for registration of 3-D shapes[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 14, 239-256(1992).

[13] Xie Z X, Xu S, Li X Y. A high-accuracy method for fine registration of overlapping point clouds[J]. Image and Vision Computing, 28, 563-570(2010).

[14] Mavridis P, Andreadis A[J]. Papaioannou G. Efficient sparse ICP. Computer Aided Geometric Design, 35/36, 16-26(2015).

[15] Attia M, Slama Y. Efficient initial guess determination based on 3D point cloud projection for ICP algorithms. [C]//2017 International Conference on High Performance Computing & Simulation (HPCS), July 17-21, 2017, Genoa, Italy. New York: IEEE(2017).

[16] Shi C Y, Liu X N, Luo X H et al. Three dimensional skull registration automatically based on partition and improved ICP[J]. Mini-Micro Systems, 39, 631-637(2018).

[17] Zhao F Q, Zhou M Q, Geng G H. Local feature registration method of skull point cloud model[J]. Journal of Image and Graphics, 22, 1120-1127(2017).

[18] Sahillioĝlu Y, Kavan L. Skuller: a volumetric shape registration algorithm for modeling skull deformities[J]. Medical Image Analysis, 23, 15-27(2015).

[19] Kybic J. Vnu ko I. Approximate all nearest neighbor search for high dimensional entropy estimation for image registration[J]. Signal Processing, 92, 1302-1316(2012).

[20] Andoni A, Indyk P. Near-optimal hashing algorithms for approximate nearest neighbor in high dimensions. [C]//2006 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS'06), October 21-24, 2006, Berkeley, CA, USA. New York: IEEE(2006).

[21] Arun K S, Huang T S, Blostein S D. Least-squares fitting of two 3-D point sets[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 5, 698-700(1987).

[22] Yuan C, Yu X Q, Luo Z Y. 3D point cloud matching based on principal component analysis and iterative closest point algorithm. [C]//2016 International Conference on Audio, Language and Image Processing (ICALIP), July 11-12, 2016, Shanghai, China. New York: IEEE(2016).

[23] Ji S J, Ren Y C, Zhao J et al. An improved method for registration of point cloud[J]. Optik, 140, 451-458(2017).

[24] Li P, Wang J, Zhao Y D et al. Improved algorithm for point cloud registration based on fast point feature histograms[J]. Journal of Applied Remote Sensing, 10, 045024(2016).

[26] Chum O, Matas J, Kittler J. Locally optimized RANSAC[M]. //Michaelis B, Krell G. Pattern recognition. Heidelberg: Springer, 2781, 236-243(2003).

[27] Mellado N, Aiger D, Mitra N J. Super 4PCS fast global pointcloud registration via smart indexing[J]. Computer Graphics Forum, 33, 205-215(2014).

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

[29] Du S Y, Liu J, Zhang C J et al. Probability iterative closest point algorithm for m-D point set registration with noise[J]. Neurocomputing, 157, 187-198(2015).

[30] Liu X H, Geng N, Zhang Z M et al. Plant point cloud registration based on improved IRLS-ICP algorithm[J]. Computer Engineering and Design, 40, 1964-1970(2019).