• Acta Photonica Sinica
  • Vol. 49, Issue 4, 0415001 (2020)
Xin-chun LI1, Zhen-yu YAN1、*, Sen LIN1、2、3, and Di JIA1
Author Affiliations
  • 1School of Electronics and Information Engineering, Liaoning Technical University, Huludao, Liaoning 125100, China
  • 2State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China
  • 3Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110016, China
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    DOI: 10.3788/gzxb20204904.0415001 Cite this Article
    Xin-chun LI, Zhen-yu YAN, Sen LIN, Di JIA. Point Cloud Registration Based on Neighborhood Characteristic Point Extraction and Matching[J]. Acta Photonica Sinica, 2020, 49(4): 0415001 Copy Citation Text show less
    References

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    [12] P JAUER, I KUHLEMANN, R BRUDER. Efficient registration of high-resolution feature enhanced point clouds. IEEE Transactions on Pattern Analysis and Machine Intelligence, 41, 1102-1115(2019).

    [13] AOKI Y, GOFTHH, SRIVATSAN R A, et al. PointLK: robust & efficient point cloud registration using point[C]. Computer Vision Pattern Recognition, 2019: 71637172.

    [15] C WANG, Y SHU, Y YANG. Point cloud registration in multidirectional affine transformation. IEEE Photonics Journal, 10, 1-15(2018).

    [16] RUSU R B, BLODOW N, BEETZ M. Fast point feature histograms (FPFH) f 3D registration[C]. IEEE International Conference on Robotics Automation, 2009: 32123217.

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    Xin-chun LI, Zhen-yu YAN, Sen LIN, Di JIA. Point Cloud Registration Based on Neighborhood Characteristic Point Extraction and Matching[J]. Acta Photonica Sinica, 2020, 49(4): 0415001
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