[1] Besl P J. McKay N. A method for registration of 3-D shapes[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 14, 239-256(1992). http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=121791

[2] Chung Y C, Su I F, Lee C et al. Multiple k nearest neighbor search[J]. World Wide Web, 20, 371-398(2017). http://dl.acm.org/citation.cfm?id=3054483

[3] Elseberg J, Magnenat S, Siegwart R et al. Comparison on nearest-neighbor-search strategies and implementations for efficient shape registration[J]. Journal of Software Engineering for Robotics, 22, 268-269(2013). http://www.researchgate.net/publication/233792571_Comparison_on_nearest-neigbour-search_strategies_and_implementations_for_efficient_shape_registration?ev=auth_pub

[4] Lv L, Sun L. An improved registration algorithm based on geometric feature for the calibration of workpiece coordinate[C]. 35 ^th Chinese Control Conference, Chengdu, Sichuan, 9475-9480(2016).

[5] Abdi H, Williams L J. Principal component analysis[J]. Wiley Interdisciplinary Reviews Computational Statistics, 2, 433-459(2010).

[6] Tao H J, Da F P. Automatic registration algorithm for the point clouds based on the normal vector[J]. Chinese Journal of Lasers, 40, 0809001(2013).

[7] Huang Y, Da F P, Tao H J. An automatic registration algorithm for point cloud based on feature extraction[J]. Chinese Journal of Lasers, 42, 0308002(2015).

[8] Wei S B, Wang S Q, Zhou C H et al. An iterative closest point algorithm based on biunique correspondence of point clouds for 3D reconstruction[J]. Acta Optica Sinica, 35, 0515003(2015).

[9] Ji S, Ren Y, Ji Z et al. An improved method for registration of point cloud[J]. International Journal for Light and Electron Optics, 140, 451-458(2017). http://www.sciencedirect.com/science/article/pii/S0030402617300517

[10] He B W, Lin Z M, Li Y F. An automatic registration algorithm for the scattered point clouds based on the curvature feature[J]. Optics & Laser Technology, 46, 53-60(2013). http://www.sciencedirect.com/science/article/pii/S0030399212001880

[11] Zeng F X, Li L, Diao X P. Iterative closest point algorithm registration based on curvature features[J]. Laser & Optoelectronics Progress, 54, 011003(2017).

[12] Chen T F, Gao C H, He B W. Point cloud registration method based on face-mating after denosing[J]. Applied Mechanics and Materials, 536, 131-135(2014). http://www.scientific.net/AMM.536-537.131

[13] Chen M L, Lu W X, Wan Y C et al. Automatic registration of terrestrial point clouds without additional information[J]. Chinese Journal of Lasers, 43, 0414003(2016).

[14] Li R Z, Yang M, Tian Y et al. Point cloud registration algorithm based on the ISS feature points combined with improved ICP algorithm[J]. Laser & Optoelectronics Progress, 54, 111503(2017).

[15] Qiao C, Ding Y L, Xu Y S et al. Image registration method based on geo-location information and precision analysis[J]. Acta Optica Sinica, 37, 0828001(2017).

[16] Wang G H, Li N, Li S. Enhanced histogram feature descriptor for automated point cloud registration[C]. 35 ^th Chinese Control Conference, Chengdu, Sichuan, 7032-7037(2016).

[17] Rusu R B, Blodow N, Beetz M. Fast point feature histograms (FPFH) for 3D registration[C]. International Conference on Robotics and Automation, Kobe, Japan, 3212-3217(2009).

[18] Shu C X, He Y T, Sun Q K. Point cloud registration based on convolutional neural network[J]. Laser & Optoelectronics Progress, 54, 031001(2017).

[19] Myronenko A, Song X. Point set registration:coherent point drift[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 32, 2262-2275(2010).

[20] Lu M, Zhao J, Guo Y et al. A 3D point cloud registration algorithm based on fast coherent point drift[C]. Applied Imagery Pattern Recognition Workshop, Washington, USA, 1-6(2015).

[21] Qu H B, Wang J Q, Li B et al. Probabilistic model for robust affine and non-rigid point set matching[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 39, 371-384(2017). http://doi.ieeecomputersociety.org/10.1109/TPAMI.2016.2545659

[22] Lawler E L, Wood D E. Branch-and-bound methods: a survey[J]. Operations Research, 14, 699-719(1966). http://dl.acm.org/citation.cfm?id=2777374

[23] Yang J, Li H, Jia Y. GO-ICP: solving 3D registration efficiently and globally optimally[C]. International Conference on Computer Vision, Sydney, Australia, 1457-1464(2013).

[24] Aiger D, Mitra N J, Cohenor D. 4-points congruent sets for robust pairwise surface registration[J]. ACM Transactions on Graphics, 27, 85(2011). http://dl.acm.org/citation.cfm?id=1360684

[25] Lei H, Jiang G, Quan L. Fast descriptors and correspondence propagation for robust global point cloud registration[J]. IEEE Transactions on Image Processing, 26, 3614-3623(2017). http://europepmc.org/abstract/MED/28475056

[26] Mian A S, Bennamoun M, Owens R. Keypoint detection and local feature matching for textured 3D face recognition[J]. International Journal of Computer Vision, 79, 1-12(2008). http://link.springer.com/article/10.1007/s11263-007-0085-5