• Laser & Optoelectronics Progress
  • Vol. 57, Issue 6, 061002 (2020)
Zhen Peng1、2, Yuanjian Lü1、2, Chao Qu1、2, and Dahu Zhu1、2、*
Author Affiliations
  • 1Hubei Key Laboratory of Advanced Automotive Components Technology, Wuhan University of Technology, Wuhan, Hubei 430070, China
  • 2Hubei Collaborative Innovation Center for Automotive Components Technology, Wuhan University of Technology, Wuhan, Hubei 430070, China
  • show less
    DOI: 10.3788/LOP57.061002 Cite this Article Set citation alerts
    Zhen Peng, Yuanjian Lü, Chao Qu, Dahu Zhu. Accurate Registration of 3D Point Clouds Based on Keypoint Extraction and Improved Iterative Closest Point Algorithm[J]. Laser & Optoelectronics Progress, 2020, 57(6): 061002 Copy Citation Text show less
    References

    [1] Wang J H, Lindenbergh R, Menenti M. SigVox: a 3D feature matching algorithm for automatic street object recognition in mobile laser scanning point clouds[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 128, 111-129(2017).

    [2] Yang P, Zhou Y H, Yao J et al. Three-dimensional shape reconstruction via an objective function optimization-based point cloud registration method[J]. Optical Engineering, 56, 113108(2017).

    [3] Yue H S, Chen W H, Wu X M et al. Extension of an iterative closest point algorithm for simultaneous localization and mapping in corridor environments[J]. Journal of Electronic Imaging, 25, 023015(2016).

    [4] Chen C S, Chen P C, Hsu C M. Three-dimensional object recognition and registration for robotic grasping systems using a modified viewpoint feature histogram[J]. Sensors, 16, 1969(2016).

    [5] Jiang Y, Huang H G, Shu Q et al. Scale point cloud registration algorithm in high-dimensional orthogonal subspace mapping[J]. Acta Optica Sinica, 39, 0315007(2019).

    [6] Ji S J, Ren Y C, Ji Z et al. An improved method for registration of point cloud[J]. Optik, 140, 451-458(2017).

    [7] Liu J, Bai D. 3D point cloud registration algorithm based on feature matching[J]. Acta Optica Sinica, 38, 1215005(2018).

    [8] Li R Z, Yang M, Tian Y et al. Point cloud registration algorithm based on the ISS feature points combined with improved ICP algorithm[J]. Laser & Optoelectronics Progress, 54, 111503(2017).

    [9] Zhong Y. Intrinsic shape signatures: a shape descriptor for 3D object recognition. [C]∥2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops, September 27-October 4, 2009, Kyoto, Japan. New York: IEEE, 689-696(2009).

    [10] Jia Y J, Xiong F G, Han X et al. Multi-scale keypoint detection based on SHOT[J]. Laser & Optoelectronics Progress, 55, 071013(2018).

    [11] Zhang Z, Xu H L, Yin H. A fast point cloud registration algorithm based on key point selection[J]. Laser & Optoelectronics Progress, 54, 121002(2017).

    [12] He B W, Lin Z M, Li Y F. An automatic registration algorithm for the scattered point clouds based on the curvature feature[J]. Optics & Laser Technology, 46, 53-60(2013).

    [13] Theiler P W, Wegner J D, Schindler K. Keypoint-based 4-points congruent sets: automated marker-less registration of laser scans[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 96, 149-163(2014).

    [14] Kleppe A L, Tingelstad L, Egeland O. Coarse alignment for model fitting of point clouds using a curvature-based descriptor[J]. IEEE Transactions on Automation Science and Engineering, 16, 811-824(2019).

    [15] 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. New York: IEEE, 3212-3217(2009).

    [16] Steder B, Rusu R B, Konolige K et al. Point feature extraction on 3D range scans taking into account object boundaries. [C]∥2011 IEEE International Conference on Robotics and Automation, May 9-13, 2011, Shanghai, China. New York: IEEE, 2601-2608(2011).

    [17] Yang J Q, Cao Z G, Zhang Q. A fast[J]. robust local descriptor for 3D point cloud registration. Information Sciences, 346/347, 163-179(2016).

    [18] 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).

    [19] Li W M, Song P F. A modified ICP algorithm based on dynamic adjustment factor for registration of point cloud and CAD model[J]. Pattern Recognition Letters, 65, 88-94(2015).

    [20] 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).

    [21] Yang J L, Li H D, Campbell D et al. Go-ICP: a globally optimal solution to 3D ICP point-set registration[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 38, 2241-2254(2016).

    [22] Mavridis P, Andreadis A[J]. Papaioannou G. Efficient sparse ICP. Computer Aided Geometric Design, 35/36, 16-26(2015).

    [23] Segal A, Haehnel D, Thrun S. Generalized-ICP[C]∥(2009).

    [24] Wu M Q, Li Z W, Zhong K et al. Adaptive point cloud registration method based on geometric features and photometric features[J]. Acta Optica Sinica, 35, 0215002(2015).

    [25] Zhao Y, Hong R C, Jiang J G. Visual summarization of image collections by fast RANSAC[J]. Neurocomputing, 172, 48-52(2016).

    [26] Lowe D G. Distinctive image features from scale-invariant keypoints[J]. International Journal of Computer Vision, 60, 91-110(2004). http://doi.ieeecomputersociety.org/resolve?ref_id=doi:10.1023/B:VISI.0000029664.99615.94&rfr_id=trans/tp/2008/10/ttp2008101683.htm

    [27] Guo Y, Zhang H L, Wang J W et al. An improved distance threshold constrainted ICP algorithm for 3D registration[J]. Journal of China Academy of Electronics and Information Technology, 6, 643-647(2011).

    [28] Stanford 3D scanning repository[EB/OL]. -08-09) [2019-06-16]. http:∥graphics.stanford.edu/data/3Dscanrep/.(2014).

    [29] Robotic 3D scan repository[EB/OL]. -10-15)[2019-06-16]. http:∥kos.informatik.uni-osnabrueck.de/3Dscans/.(2016).

    [30] Hu X X, Zhang L. Improved 3D-NDT multi-viewpoint cloud registration combined with NARF features[J]. Signal Processing, 31, 1675-1679(2015).

    [31] Theiler P W, Wegner J D, Remote Sensing, Spatial Information Sciences. II-, 5/W2, 283-288(2013).

    [32] Fitzgibbon A W. Robust registration of 2D and 3D point sets[J]. Image and Vision Computing, 21, 1145-1153(2003).

    [33] Magnusson M. The three-dimensional normal-distributions transform: an efficient representation for registration, surface analysis, and loop detection[D]. Örebro: Örebro Universitet, 1-5(2009).

    [34] Lei H, Jiang G, Quan L. Fast descriptors and correspondence propagation for robust global point cloud registration[J]. IEEE Transactions on Image Processing, 26, 3614-3623(2017).

    Zhen Peng, Yuanjian Lü, Chao Qu, Dahu Zhu. Accurate Registration of 3D Point Clouds Based on Keypoint Extraction and Improved Iterative Closest Point Algorithm[J]. Laser & Optoelectronics Progress, 2020, 57(6): 061002
    Download Citation