[1] LI Y, TONG G F, YANG J C et al. 3D point cloud scene data acquisition and its key technologies for scene understanding[J]. Laser & Optoelectronics Progress, 56, 040002(2019).

[2] DAI J L. A research on preprocessing algorithms of mass point cloud[D](2006).

[3] LI J W, ZHAN J W. Review on 3D point cloud registration method[J]. Journal of Image and Graphics, 27, 349-367(2022).

[4] YANG J Q, ZHANG S K, FAN S C et al. Survey on multi-view point cloud registration algorithm[J]. Journal of Huazhong University of Science and Technology (Natural Science Edition), 50, 16-34(2022).

[5] 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).

[6] WEI L, XUE M Y, HUO J et al. Non-cooperative target feature point cloud registration optimization based on ICP algorithm[J]. Journal of System Simulation, 32, 2383-2387(2020).

[7] ZHANG X C, ZHOU H J, ZHENG J J et al. Point cloud registration based on multi-scale feature and point distance constraint[J]. Laser & Optoelectronics Progress, 58, 2415004(2021).

[8] SUN S F, LI Z, XIA K et al. Variable scale point cloud registration algorithm[J]. Journal of System Simulation, 30, 2465-2474(2018).

[9] WANG B, LIU L, HOU Y Q et al. Three-dimensional cardiac point cloud registration by improved iterative closest point method[J]. Optics and Precision Engineering, 28, 474-484(2020).

[10] ZHANG J Y, YAO Y X, DENG B L. Fast and robust iterative closest point[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 44, 3450-3466(2022).

[11] SUN Y, BABU P, PALOMAR D P. Majorization-minimization algorithms in signal processing, communications, and machine learning[J]. IEEE Transactions on Signal Processing, 65, 794-816(2017).

[12] SALTI S, TOMBARI F, DI STEFANO L. SHOT: unique signatures of histograms for surface and texture description[J]. Computer Vision and Image Understanding, 125, 251-264(2014).

[13] YANG J Q, CAO Z G, ZHANG Q. A fast and robust local descriptor for 3D point cloud registration[J]. Information Sciences, 346-347, 163-179(2016).

[14] LI X C, YAN Z Y, LIN S et al. Point cloud registration based on neighborhood characteristic point extraction and matching[J]. Acta Photonica Sinica, 49, 0415001(2020).

[15] LIU Y Z, ZHANG Q, LIN S. Improved ICP point cloud registration algorithm based on fast point feature histogram[J]. Laser & Optoelectronics Progress, 58, 0611003(2021).

[16] ZHAO Y T, QI J X, LI W G et al. Point cloud registration based on improved 3DSC[J]. Chinese Journal of Liquid Crystals and Displays, 37, 1590-1597(2022).

[17] RUSU R B, BLODOW N, BEETZ M. Fast point feature histograms (FPFH) for 3D registration[C], 3212-3217(2009).

[18] HU Q Y, YANG B, XIE L H et al. RandLA-Net: efficient semantic segmentation of large-scale point clouds[C], 11105-11114(2020).

[19] ZHONG Y. Intrinsic shape signatures: a shape descriptor for 3D object recognition[C], 689-696(2009).

[20] JOHNSON A E, HEBERT M. Using spin images for efficient object recognition in cluttered 3D scenes[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 21, 433-449(1999).

[21] LEVOY M, GERTH J, CURLESS B et al. The Stanford 3D scanning repository[EB/OL]. https://graphics.stanford.edu/data/3Dscanrep/

[22] TANG Z R, LIU M Z, WANG C et al. Point cloud registration based on multi-dimensional mixed Cauchy distribution[J]. Acta Optica Sinica, 39, 398-410(2019).