[1] Luo Y, Guan T, Wei B et al. Fast terrain mapping from low altitude digital imagery[J]. Neurocomputing, 156, 105-116(2015).

[2] Wang J C, Wang T M, Xu Y et al. Registration method based on ICP algorithm for 3D surgical navigation[J]. Journal of Beijing University of Aeronautics and Astronautics, 35, 434-438(2009).

[3] Bidanda B, Hosni Y A. Reverse engineering and its relevance to industrial engineering: a critical review[J]. Computers & Industrial Engineering, 26, 343-348(1994).

[4] 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).

[5] Yan J F, Deng K Z, Xing Z Q[J]. 3D laser scanning point cloud filtering based on least squares fitting Bulletin of Surveying and Mapping, 2013, 43-46.

[6] Liu J, Bai D. 3D point cloud registration algorithm based on feature matching[J]. Acta Optica Sinica, 38, 1215005(2018).

[7] Chen X, He B W. A fast global registration algorithm based on correcting point cloud principal component coordinate system[J]. Laser & Optoelectronics Progress, 55, 061003(2018).

[8] Ou X L, Kuang X L, Ni W Y. Summarization on 3D scattered point cloud segmentation[J]. Journal of Hunan University of Technology, 24, 45-49(2010).

[9] He H G, Tian J, Zhao M C et al. A 3D medical imaging surface reconstruction scheme based on segmentation[J]. Journal of Software, 13, 219-226(2002).

[10] Li P, Xing S, Li J et al. A three-dimensional laser point cloud rough registration algorithm based on virtual feature points[J]. Journal of Geo-Information Science, 20, 430-439(2018).

[11] Zhang X, Zhang R, Zhang X C. Matching method of point cloud models based on auxiliary device[J]. Computer Integrated Manufacturing Systems, 20, 1029-1034(2014).

[12] Yang Z H, Zhang Y S. A global registration method of terrestrial laser point cloud based on feature points[J]. Geomatics & Spatial Information Technology, 41, 66-68, 71(2018).

[13] Li B F, Tian B H, Zhang X M et al. Accelerator of the global automated image registration algorithm[J]. Journal of Computer-Aided Design & Computer Graphics, 24, 1363-1368(2012).

[14] Chen C S, Hung Y P, Cheng J B. RANSAC-based DARCES: a new approach to fast automatic registration of partially overlapping range images[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 21, 1229-1234(1999).

[15] Zhang X, Zhang A, Wang Z H. Point cloud registration based on improved normal distribution transform algorithm[J]. Laser & Optoelectronics Progress, 51, 041002(2014).

[16] Tangelder J W H, Veltkamp R C. A survey of content based 3D shape retrieval methods[J]. Multimedia Tools and Applications, 39, 441-471(2008).

[17] Yan J F, Deng K Z[J]. Point cloud registration algorithm based on extracting and matching feature points Bulletin of Surveying and Mapping, 2013, 62-65.

[18] Lun J, Peng Z T, Dong D L et al[J]. The registration algorithm of point cloud based on optimal extraction of FPFH feature New Industrialization Straregy, 2014, 75-81.

[19] Aiger D, Mitra N J, Cohen-Or D. 4-points congruent sets for robust pairwise surface registration[J]. ACM Transactions on Graphics, 27, 85(2008).

[20] 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, 312-319(2017).

[21] Biber P, Strasser W. The normal distributions transform: a new approach to laser scan matching. Cat. No.03CH37453), October 27-31, 2003, Las Vegas, Nevada, USA. New York: IEEE, 2743-2748(2003).