[1] Janai J, Güney F, Behl A et al. Computer vision for autonomous vehicles: problems, datasets and state of the art[J]. Foundations and Trends® in Computer Graphics and Vision, 12, 1-308(2020). http://www.researchgate.net/publication/343469825_Computer_Vision_for_Autonomous_Vehicles_Problems_Datasets_and_State_of_the_Art
[2] Geman D, Geman S, Hallonquist N et al. Visual turing test for computer vision systems[J]. Proceedings of the National Academy of Sciences, 112, 3618-3623(2015).
[3] Akhtar N, Mian A. Threat of adversarial attacks on deep learning in computer vision: a survey[J]. IEEE Access, 6, 14410-14430(2018). http://ieeexplore.ieee.org/document/8294186/
[4] Dai A, Nießner M, Zollhöfer M et al. BundleFusion: real-time globally consistent 3D reconstruction using on-the-fly surface reintegration[J]. ACM Transactions on Graphics, 36, 76a(2017). http://dl.acm.org/doi/abs/10.1145/3072959.3054739
[5] Zhang P C, Liu J, Yang H M et al. Laser overlapping three-dimensional reconstruction of damaged aero engine blade[J]. Laser & Optoelectronics Progress, 57, 161504(2020).
[6] Song X L, Li S, Gu M T et al. Three-dimensional reconstruction of micro-scale flow field based on light field microscopic imaging[J]. Acta Optica Sinica, 39, 1011002(2019).
[7] 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).
[8] Rusu R B, Blodow N, Beetz M. Fast point feature histograms (FPFH) for 3D registration[C]∥2009 IEEE International Conference on Robotics and Automation, May 12-17, 2009, Kobe, Japan., 3212-3217(2009).
[9] Zhang B, Xiong C B. Automatic point cloud registration based on voxel downsampling and key point extraction[J]. Laser & Optoelectronics Progress, 57, 041008(2020).
[10] Xue S, Zhang Z, Lv Q et al. Point cloud registration method for pipeline workpieces based on PCA and improved ICP algorithms[J]. IOP Conference Series: Materials Science and Engineering, 612, 032188(2019). http://www.researchgate.net/publication/336671754_Point_Cloud_Registration_Method_for_Pipeline_Workpieces_Based_on_PCA_and_Improved_ICP_Algorithms
[11] Bentley J L. Multidimensional binary search trees used for associative searching[J]. Communications of the ACM, 18, 509-517(1975).
[12] Greenspan M, Yurick M. Approximate k-d tree search for efficient ICP[C]∥Fourth International Conference on 3-D Digital Imaging and Modeling, 2003. 3DIM 2003. Proceedings, October 6-10, 2003, Banff, Alta., Canada., 442-448(2003).
[13] Jost T, Hugli H. A multi-resolution ICP with heuristic closest point search for fast and robust 3D registration of range images[C]∥Fourth International Conference on 3-D Digital Imaging and Modeling, 2003.3DIM 2003. P, 427-433(2003).
[14] Guan W, Li W T, Ren Y. Point cloud registration based on improved ICP algorithm[C]∥2018 Chinese Control And Decision Conference (CCDC), June 9-11, 2018, Shenyang, China., 1461-1465(2018).
[15] Li X C, Yan Z Y, Lin S. Point cloud registration based on weighting information of neighborhood surface deformation[J]. Laser & Optoelectronics Progress, 57, 141102(2020).
[16] Peng Z, Lü Y J, Qu C et al. Accurate registration of 3D point clouds based on keypoint extraction and improved iterative closest point algorithm[J]. Laser & Optoelectronics Progress, 57, 061002(2020).
[17] Wang Y, Zou H, He Y M et al. ICP algorithm based on multi-resolution registration point[J]. Journal of Chinese Computer Systems, 39, 406-410(2018).
[18] Tang Z R, Jiang Y, Miao C W et al. Three-dimensional point cloud registration algorithm based on factor analysis[J]. Laser & Optoelectronics Progress, 56, 191503(2019).
[19] 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).
[20] Xue S, Zhang Z, Meng X Y et al. Point cloud registration method for pipeline workpieces based on RANSAC and improved ICP algorithms[J]. IOP Conference Series: Materials Science and Engineering, 612, 032190(2019). http://www.researchgate.net/publication/337873041_Point_Cloud_Registration_Method_for_Pipeline_Workpieces_Based_On_NDT_and_Improved_ICP_Algorithms