Laser & Infrared, Volume. 54, Issue 10, 1569(2024)

Point cloud registration method based on binary depth image descriptors

JIANG Zheng-yuan, CAI Yu, YANG Jun-cheng*, and FAN Dan
Author Affiliations
  • Yunnan Institute of Water & Hydropower Engineering Investigation, Design and Research, Kunming 650021, China
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    References(19)

    [1] [1] Quan S, Ma J, Hu F, et al. Local voxelized structure for 3D binary feature representation and robust registration of point clouds from low-cost sensors[J]. Information Sciences, 2018, 444: 153-171.

    [2] [2] Li J Y. A practical outlier removal method for correspondence-based point cloud registration clouds from low-cost sensors[J]. IEEE Transactions on Pattern Analysis & Machine Intelligence, 2022, 44(18): 3926-3939.

    [4] [4] Besl P J, Mckay H D. A method for registration of 3-D shapes[J]. IEEE Transactions on Pattern Analysis & Machine Intelligence, 1992(2): 239-256.

    [5] [5] Lv C, Lin W, Zhao B. KSS-ICP: point cloud registration based on Kendall shape space[J]. IEEE Transactions on Image Processing, 2023, 32: 1681-1693.

    [6] [6] Shi X, Liu T, Han X. Improved iterative closest point (ICP) 3D point cloud registration algorithm based on point cloud filtering and adaptive fireworks for coarse registration[J]. International Journal of Remote Sensing, 2020, 41(8): 3197-3220.

    [7] [7] Johnson A E, Hebert M. Using spin images for efficient object recognition in cluttered 3D scenes[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1999, 21(5): 433-449.

    [8] [8] Rusu R B, Blodow N, Beetz M. Fast point feature histograms (FPFH) for 3D registration[C]//: IEEE International Conference on Robotics and Automation. 2009.

    [9] [9] Guo Y L, Sohel F B M, Liu M, et al. Rotational projection statistics for 3D local surface description and object recognition[J]. International Journal of Computer Vision, 2013, 105: 63-86.

    [10] [10] Yang J Q, Zhang Q, Xiao Y, et al. Toldi: an effective and robust approach for 3D local shape description[J]. Pattern Recognition, 2017, 65: 175-187.

    [11] [11] Yang J Q, Zhang Q, Xian K, et al. Rotational contour signatures for both real-valued and binary feature representations of 3D local shape[J]. Computer Vision and Image Understanding, 2017, 160: 133-147.

    [12] [12] Calonder M, Lepetit V, Ozuysal M, et al. Brief: computing a local binary descriptor very fast[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2012, 34(7): 1281-1298.

    [13] [13] Rublee E, Rabaud V, Konolige K, et al. Orb: an efficient alternative to sift or surf[C]//: IEEE International Conference on Computer Vision (ICCV), 2011.

    [14] [14] Prakhya S M, Liu B B, Lin W S, et al. B-shot: a binary feature descriptor for fast and efficient keypoint matching on 3D point clouds[J]. Autonomous Robots, 2017, 41(7): 1501-1520.

    [15] [15] Tombari F, Salti S, Di Stefano L. Shot: unique signatures of histograms for surface and texture description[J]. Computer Vision and Image Understanding, 2014, 125: 251-264.

    [16] [16] Dong Z, Yang B S, Liu Y, et al. A novel binary shape context for 3D local surface description[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2017, 130: 431-452.

    [20] [20] Guo Y L, Bennamoun M, Sohel F, et al.3D object recognition in cluttered scenes with local surface features: a survey[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2014, 36(11): 2270-2287.

    [21] [21] Mian A, M B, Owens R. On the repeatability and quality of keypoints for local feature-based 3D object retrieval from cluttered scenes[J]. International Journal of Computer Vision, 2010, 89(2): 348-361.

    [23] [23] Zou Y W X Z T, Delearde R, Kurtz C, et al. Broph: an efficient and compact binary descriptor for 3D point clouds[J]. Pattern Recognition, 2018, 76: 522-536.

    [24] [24] Dong Z, Liang F X, Yang B S, et al. Registration of large-scale terrestrial laser scanner point clouds: a review and benchmark[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2020, 163: 327-342.

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    JIANG Zheng-yuan, CAI Yu, YANG Jun-cheng, FAN Dan. Point cloud registration method based on binary depth image descriptors[J]. Laser & Infrared, 2024, 54(10): 1569

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    Paper Information

    Category:

    Received: Dec. 5, 2023

    Accepted: Apr. 23, 2025

    Published Online: Apr. 23, 2025

    The Author Email: YANG Jun-cheng (744943993@qq.com)

    DOI:10.3969/j.issn.1001-5078.2024.10.010

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