[1] Weir D J, Milroy M J, Bradley C et al. Reverse engineering physical models employing wrap-around B-spline surfaces and quadrics[J]. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 210, 147-157(1996).

[2] Han H Y, Han X, Sun F S et al. Point cloud simplification with preserved edge based on normal vector[J]. Optik, 126, 2157-2162(2015).

[3] He M F, Zhou L S, Shen H C. Curvature estimation of scattered-point cloud data and its application[J]. Journal of Nanjing University of Aeronautics & Astronautics, 37, 515-519(2005).

[4] Wang L H, Chen J, Yuan B Z. Simplified representation for 3D point cloud data[C], 1271-1274(2010).

[5] Li R B, Yuan X P, Gan S et al. Point cloud simplification optimization strategy and experimental research based on multiple algorithms[J]. Laser & Optoelectronics Progress, 57, 231402(2020).

[6] Zhou Y, Zhang W B, Du F R et al. Algorithm for reduction of scattered point cloud data based on curvature[J]. Transactions of Beijing Institute of Technology, 30, 785-789(2010).

[7] Chen H, Huang X M, Liu W Q. Laser point cloud simplification algorithm based on dynamic grid k-nearest neighbors searching[J]. Control and Decision, 35, 2986-2992(2020).

[8] Fu S Y, Wu L S, Chen H W. Point cloud simplification method based on space grid dynamic partitioning[J]. Acta Optica Sinica, 37, 1115007(2017).

[9] Yang Q X, Yang X Q, Du J. Point cloud simplification algorithm based on Hausdorff distance and segmentation[J]. Computer Engineering and Design, 37, 2105-2109(2016).

[10] Wang J Q, Fan Y G, Li G S et al. Adaptive point cloud reduction based on multi parameter k-means clustering[J]. Laser & Optoelectronics Progress, 58, 0610008(2021).

[11] Zheng R D, Li J L, Zhang Y et al. Scattered point cloud simplification algorithm based on adaptive neighborhood and local contribution value[J]. Laser & Optoelectronics Progress, 58, 1610019(2021).

[12] Li J, Cao Y, Wang Z M et al. Scattered point cloud simplification algorithm integrating k-means clustering and Hausdorff distance[J]. Geomatics and Information Science of Wuhan University, 45, 250-257(2020).

[13] Chen Z W, Da F P. 3D point cloud simplification algorithm based on fuzzy entropy iteration[J]. Acta Optica Sinica, 33, 0815001(2013).

[14] Mahdaoui A, Bouazi A, Hsaini A M et al. Comparison of K-means and fuzzy C-means algorithms on simplification of 3D point cloud based on entropy estimation[J]. Advances in Science, Technology and Engineering Systems Journal, 2, 38-44(2017).

[15] Zhang S B, Yang B S, Liang F X. Point cloud simplification considering geometric morphology and density distribution[J]. Geomatics Science and Technology, 212-222(2018).

[16] Hoppe H, DeRose T, Duchamp T et al. Surface reconstruction from unorganized points[C], 71-78(1992).

[17] Besl P J, Jain R C. Segmentation through variable-order surface fitting[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 10, 167-192(1988).

[18] Sra S. A short note on parameter approximation for von Mises-Fisher distributions: and a fast implementation of Is(x)[J]. Computational Statistics, 27, 177-190(2012).

[19] Zhang W M, Wu X, Gao Y K et al. A simplification algorithm for point cloud based on feature extraction[J]. Optical Technique, 44, 733-738(2018).

[20] Banerjee A, Dhillon I S, Ghosh J et al. Clustering on the unit hypersphere using von Mises-Fisher distributions[J]. Journal of Machine Learning Research, 6, 1345-1382(2005).

[21] An S. Research on the simplification of center of gravity in point cloud region based on Octree[D](2018).

[22] Shi B Q, Liang J, Liu Q. Adaptive simplification of point cloud using k-means clustering[J]. Computer-Aided Design, 43, 910-922(2011).