Journal of Applied Optics, Volume. 44, Issue 2, 330(2023)

Point cloud registration algorithm based on 3D shape context features

Zixiang ZHOU1, Dandan HUANG1、*, and Zhi LIU2
Author Affiliations
  • 1School of Electronical and Information Engineering, Changchun University of Science and Technology, Changchun 130000, China
  • 2Institute of Space Optoelectronics Technology, Changchun University of Science and Technology, Changchun 130000, China
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    References(6)

    [2] [2] TAMAKI T, ABE M, RAYTCHEV B, et al. Softassign and EM-ICP on GPU[C]. Proceedings of International Conference on Net working And Computing. USA: IEEE, 2010: 179-183.

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    [4] [4] MAGNUSSON M, LILIENTHAL, A. J, DUCKETT T. Scan registration for autonomous mining vehicles using 3D-NDT[J]. Field Robot, 2007, 24(2): 803–827.

    [6] [6] HAN Yifei, YANG Zi, QIAN Zhengfu, et al, Improved point cloud registration algorithm based on fpfh and normal vector[J]. Semiconductor Optoelectronics, 2021, 42(4): 579-584.

    [9] [9] YU Z. Intrinsic shape signatures: a shape descriptor for 3D object recognition[C]//Proceedings of the 12th IEEE International Conference on Computer Vision Workshops(ICCV Workshops). Kyoto: IEEE, 2009: 689-696.

    [12] [12] TOMBARI F, SALTI S, STEFANO L. Unique shape context for 3D data description[C]. Proceedings of the ACM workshop on 3D object retrieval. [S. l. ]: ACM, 2010: 57-62.

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    Zixiang ZHOU, Dandan HUANG, Zhi LIU. Point cloud registration algorithm based on 3D shape context features[J]. Journal of Applied Optics, 2023, 44(2): 330

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    Paper Information

    Category: Research Articles

    Received: May. 9, 2022

    Accepted: --

    Published Online: Apr. 14, 2023

    The Author Email: HUANG Dandan (hdd@cust.edu.cn)

    DOI:10.5768/JAO202344.0202005

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