• Laser & Optoelectronics Progress
  • Vol. 57, Issue 14, 141102 (2020)
Xinchun Li1, Zhenyu Yan1、*, and Sen Lin1、2、3
Author Affiliations
  • 1School of Electronic and Information Engineering, Liaoning Technical University, Huludao, Liaoning 125100, China
  • 2State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, Liaoning 110016, China
  • 3Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang, Liaoning 110016, China
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    DOI: 10.3788/LOP57.141102 Cite this Article Set citation alerts
    Xinchun Li, Zhenyu Yan, Sen Lin. Point Cloud Registration Based on Weighting Information of Neighborhood Surface Deformation[J]. Laser & Optoelectronics Progress, 2020, 57(14): 141102 Copy Citation Text show less
    References

    [1] Wu L H, Huang H. Survey on points-driven computer graphics[J]. Journal of Computer-Aided Design & Computer Graphics, 27, 1341-1353(2015).

    [2] 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).

    [3] Liu B, Gao X H, Liu H D et al. A fast weighted registration method of 3D point cloud based on curvature feature. [C]∥Proceedings of the 3rd International Conference on Multimedia and Image Processing-ICMIP 2018, March 16-18, 2018, Guiyang, China. New York: ACM, 83-87(2018).

    [4] Zhang B, Xiong C B. Automatic point cloud registration based onvoxel downsampling and key point extraction[J]. Laser & Optoelectronics Progress, 57, 041008(2020).

    [5] Ma Z L, Zhou M Q, Geng G H et al. Automatic registration algorithm for scattered point clouds based on curvature feature[J]. Application Research of Computers, 32, 1878-1880, 1887(2015).

    [6] Wang S, Sun H Y, Guo H C. Overlapping region extraction method for laser point clouds registration[J]. Infrared and Laser Engineering, 46, s126002(2017).

    [7] Tombari F. Salti S, di Stefano L. Unique signatures of histograms for local surface description[M]. ∥Daniilidis K, Maragos P, Paragios N. Computer vision-ECCV 2010. Lecture notes in computer science. Berlin: Springer, 6313, 356-369(2010).

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

    [9] Zeng F X, Li L, Diao X P. Terative closest point algorithm registration based on curvature features[J]. Laser & Optoelectronics Progress, 54, 011003(2017).

    [10] 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).

    [11] He Y, Liang B, Yang J et al. Aniterative closest points algorithm for registration of 3D laser scanner point clouds with geometric features[J]. Sensors, 17, 1862(2017).

    [12] Elbaz G, Avraham T, Fischer A. 3D point cloud registration for localization using a deep neural network auto-encoder. [C]∥2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), July 21-26, 2017, Honolulu, HI, USA. New York: IEEE, 2472-2481(2017).

    [13] Jauer P, Kuhlemann I, Bruder R et al. Efficient registration of high-resolution feature enhanced point clouds[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 41, 1102-1115(2019).

    [14] Lu J, Fan Z J, Wang W J. Fast point cloud splicing algorithm based on weighted neighborhood information of points[J]. Journal of Computer-Aided Design & Computer Graphics, 31, 1238-1246(2019).

    [15] Ge B Z, Zhou T Y, Chen L et al. Point clouds registration algorithm based on improved ISS feature points and artificial bee colony algorithm[J]. Journal of Tianjin University, 49, 1296-1302(2016).

    [16] Tao H J, Da F P. Automatic registration algorithm for the point clouds based on the normal vector[J]. Chinese Journal of Lasers, 40, 0809001(2013).

    [17] Yuan Z C, Lu T D, Deng X Y. Comparison of parameter estimation methods for rigid motion of point cloud[J]. Engineering of Surveying and Mapping, 27, 34-40(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] 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).

    [21] 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).

    Xinchun Li, Zhenyu Yan, Sen Lin. Point Cloud Registration Based on Weighting Information of Neighborhood Surface Deformation[J]. Laser & Optoelectronics Progress, 2020, 57(14): 141102
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