Laser & Infrared, Volume. 55, Issue 2, 296(2025)

Point cloud registration based on improved 3DSIFT algorithm

ZHANG Ping-jun and ZHAO Hao*
Author Affiliations
  • School of Electronic, Electrical Engineering and Physics, Fujian University of Technology, Fuzhou 350118, China
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    References(10)

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    [6] [6] X. Huang, G. Mei, J. Zhang, et al. Feature-metric registration: a fast semi-supervised approach for robust point cloud registration without correspondences[C]//2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Seattle, WA, USA, 2020: 11363-11371.

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    [10] [10] Ghorbani, Fariborz and Ebadi, Hamid and Sedaghat, et al. A novel 3-D local daisy-style descriptor to reduce the effect of point displacement error in point cloud registration[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022, 15: 2254-2273.

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    ZHANG Ping-jun, ZHAO Hao. Point cloud registration based on improved 3DSIFT algorithm[J]. Laser & Infrared, 2025, 55(2): 296

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    Paper Information

    Category:

    Received: Jul. 2, 2024

    Accepted: Apr. 3, 2025

    Published Online: Apr. 3, 2025

    The Author Email: ZHAO Hao (hzhao1915@163.com)

    DOI:10.3969/j.issn.1001-5078.2025.020

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