[1] Huang L, Chen S Y, Zhang J F et al. Real-time motion tracking for indoor moving sphere objects with a LiDAR sensor[J]. Sensors, 17, 1932(2017). http://europepmc.org/abstract/MED/28832520

[2] Douillard B, Underwood J, Vlaskine V et al. A pipeline for the segmentation and classification of 3D point clouds[M]. ∥Khatib O, Kumar V, Sukhatme G. Experimental robotics. Berlin, Heidelberg: Springer, 585-600(2014).

[3] Lu X H, Yao J, Tu J G, Remote Sensing, Spatial Information Scienceset al. Pairwise linkage for point cloud segmentation[J]. III-, 3, 201-208(2016).

[4] Klasing K, Wollherr D, Buss M. A clustering method for efficient segmentation of 3D laser data. [C]∥2008 IEEE International Conference on Robotics and Automation, May 19-23, 2008, Pasadena, CA, USA. New York: IEEE, 4043-4048(2008).

[5] Luo Z, Habibi S, Mohrenschildt M. LiDAR based real time multiple vehicle detection and tracking[J]. World Academy of Science, Engineering and Technology, International Journal of Computer, Electrical, Automation, Control and Information Engineering, 10, 1125-1132(2016). http://www.waset.org/abstracts/43729

[6] Huang G, Wu C Z, Lü N C et al. A study of laser radar object detection based on improved DBSCAN algorithm[J]. Journal of Transport Information and Safety, 33, 23-28(2015).

[7] Asvadi A, Premebida C, Peixoto P et al. 3D Lidar-based static and moving obstacle detection in driving environments: an approach based on voxels and multi-region ground planes[J]. Robotics and Autonomous Systems, 83, 299-311(2016).

[8] Yang F, Zhu Z, Gong X J et al. Real-time dynamic obstacle detection and tracking using 3D Lidar[J]. Journal of Zhejiang University(Engineering Science), 46, 1565-1571(2012).

[9] Ye G. Multi-target detection and tracking algorithm for autonomous driving car based on a 3D lidar in urban traffic environment[D]. Beijing: Beijing Institute of Technology(2016).

[10] Börcs A, Nagy B, Benedek C. Fast 3-D urban object detection on streaming point clouds[M]. ∥Agapito L, Bronstein M, Rother C. Lecture notes in computer science. Cham: Springer, 8926, 628-639(2015).

[11] Moosmann F, Pink O, Stiller C. Segmentation of 3D lidar data in non-flat urban environments using a local convexity criterion. [C]∥2009 IEEE Intelligent Vehicles Symposium, June 3-5, 2009, Xi'an, China. New York: IEEE, 215-220(2009).

[12] Hui Z Y, Cheng P G, Guan Y L et al. Review on airborne LiDAR point cloud filtering[J]. Laser & Optoelectronics Progress, 55, 060001(2018).

[13] Chu P, Cho S, Sim S et al. A fast ground segmentation method for 3D point cloud[J]. Journal of Information Processing Systems, 13, 491-499(2017).

[14] Huang Z W, Liu F, Hu G W. Improved method for LiDAR point cloud data filtering based on hierarchical pseudo-grid[J]. Acta Optica Sinica, 37, 0828004(2017).

[15] Wang X, Wang J Q, Li K Q et al. Fast segmentation of 3-D point clouds for intelligent vehicles[J]. Journal of Tsinghua University (Science and Technology), 54, 1440-1446(2014).

[16] Bogoslavskyi I, Stachniss C. Efficient online segmentation for sparse 3D laser scans[J]. PFG-Journal of Photogrammetry, Remote Sensing and Geoinformation Science, 85, 41-52(2017).

[17] Yuan X, Zhao C X. A laser point cloud clustering algorithm for robot navigation[J]. Robot, 33, 90-96(2011).

[18] Moosmann F[M]. Interlacing self-localization, moving object tracking and mapping for 3D range sensors(2013).