［1］CHOURASIYA S, MOHAPATRA P K, TRIPATHI S. Non-intrusive underwater measurement of mobile bottom surface［J］. Advances in Water Resources, 2017, 104: 76-88.
［2］KRZESZOWSKI T, DZIADEK B, FRANCA C, et al. System for estimation of human anthropometric parameters based on data from kinect v2 depth camera［J］. Sensors, 2023, 23(7): 3459.
［3］苏云龙,平雪良,李楠.基于RANSAC三维点云的平面提取算法［J］.激光与红外, 2019,49(6):780-784.
SU Y L, PING X L, LI N. A planar extraction algorithm based on RANSAC 3D point cloud［J］. Laser & Infrared, 2019,49(6):780-784. (in Chinese)
［4］SEVGENS C, KARSLI F. An improved RANSAC algorithm for extracting roof planes from airborne lidar data［J］. The Photogrammetric Record, 2020, 35(169): 40-57.
［5］刘亚坤,李永强,刘会云,等.基于改进RANSAC算法的复杂建筑物屋顶点云分割［J］.地球信息科学学报,2021,23(8):1497-1507.
LIU Y K, LI Y Q, LIU H Y, et al. An improved RANSAC algorithm for point cloud segmentation of complex building roofs［J］. Journal of Geo-information Science, 2021,23(8):1497-1507. (in Chinese)
［6］WANG B X, LAN J, GAO J J. LiDAR filtering in 3D object detection based on improved RANSAC［J］. Remote Sensing, 2022, 14(9): 2110. 
［7］KUAK R A. The feature extraction from point clouds using geometric features and RANSAC algorithm［J］. Advanced LiDAR, 2022, 2(1): 15-20.
［8］DU X G, LU Y C, CHEN Q J. A fast multiplane segmentation algorithm for sparse 3D LiDAR point clouds by line segment grouping［J］. IEEE Transactions on Instrumentation and Measurement, 2023, 72: 1-15.
［9］LI L, YAO J, TU J M, et al. Roof plane segmentation from airborne LiDAR data using hierarchical clustering and boundary relabeling［J］. Remote Sensing, 2020, 12(9): 1363.
［10］SUN Z, LI Z Y, LIU Y C. An improved lidar data segmentation algorithm based on Euclidean clustering［C］//Proceedings of the 11th International Conference on Modelling, Identification and Control (ICMIC2019). Singapore：Springer , 2020: 1119-1130.
［11］ZHAO Y P, ZHOU X L. K-means clustering algorithm and its improvement research［J］. Journal of Physics: Conference Series, 2021, 1873(1): 012074.
［12］史红霞,王建民.基于法向量区域聚类分割的点云特征线提取［J］.中国机械工程,2021,32(21):2552-2561.
SHI H X, WANG J M. Feature line extraction for point cloud based on normal vector region clustering segmentation［J］. China Mechanical Engineering, 2021,32(21):2552-2561. (in Chinese)
［13］LEE H R, JUNG J Y. Clustering-based plane segmentation neural network for urban scene modeling［J］. Sensors, 2021, 21(24): 8382.
［14］HARJANTI T W, SETIYANI H, TRIANTO J, et al. Classification of mint leaf types based on the image using Euclidean distance and K-means clustering with shape and texture feature extraction［J］. Tech-E, 2022,  5(2):115-124.
［15］XIE Y X, TIAN J J, ZHU X X. Linking points with labels in 3D: a review of point cloud semantic segmentation［J］. IEEE Geoscience and Remote Sensing Magazine, 2020, 8(4): 38-59.
［16］李仁忠,刘阳阳,杨曼,等.基于改进的区域生长三维点云分割［J］.激光与光电子学进展, 2018,55(5):325-331.
LI R Z, LIU Y Y, YANG M, et al. Three-dimensional point cloud segmentation algorithm based on improved region growing［J］. Laser & Optoelectronics Progress, 2018,55(5):325-331. (in Chinese)
［17］汪文琪,李宗春,付永健,等.基于改进多规则区域生长的点云多要素分割［J］.光学学报, 2021,41(5):198-212.
WANG W Q, LI Z C, FU Y J, et al. Multi-factor segmentation of point cloud based on improved multi-rule region growing［J］. Acta Optica Sinica, 2021,41(5):198-212. (in Chinese)
［18］赵传,郭海涛,卢俊,等.结合区域增长与RANSAC的机载LiDAR点云屋顶面分割［J］.测绘学报, 2021,50(5):621-633.
ZHAO C, GUO H T, LU J, et al. Roof segmentation from airborne LiDAR by combining region growing with random sample consensus［J］.Acta Geodaetica et Cartographica Sinica, 2021，50(5):621-633. (in Chinese)
［19］李文,刘德儿,王有毅,等.基于超体素的区域聚类的复杂场景分割［J］.激光与红外, 2021,51(11):1425-1432.
LI W, LIU D E, WANG Y Y, et al. Complex scene segmentation based on super voxel region clustering［J］. Laser & Infrared, 2021,51(11):1425-1432. (in Chinese)
［20］WANG M, TSENG Y H. Automatic segmentation of LiDAR data into coplanar point clusters using an octree-based split and merge algorithm［J］. Photogrammetric Engineering & Remote Sensing, 2010, 76(4): 407-420.
［21］VO A V, TRUONG-HONG L, LAEFER D F, et al. Octree-based region growing for point cloud segmentation［J］. ISPRS Journal of Photogrammetry and Remote Sensing, 2015, 104: 88-100.
［22］李明磊,李广云,王力,等.采用八叉树体素生长的点云平面提取［J］.光学精密工程, 2018,26(1):172-183.
LI M L, LI G Y, WANG L, et al. Planar feature extraction from unorganized point clouds using octree voxel based region growing［J］. Optics and Precision Engineering, 2018,26(1):172-183. (in Chinese)
［23］SU Y T, BETHEL J, HU S W. Octree-based segmentation for terrestrial LiDAR point cloud data in industrial applications［J］. ISPRS Journal of Photogrammetry & Remote Sensing, 2016, 113:59-74.
［24］ZENG J H，WANG D C，CHEN P. Improved color region growing point cloud segmentation algorithm based on Octree［C］// 2022 3rd International Conference on Information Science, Parallel and Distributed Systems(ISPDS).New York:IEEE,2022:424-429.