Laser & Optoelectronics Progress, Volume. 58, Issue 4, 0410011(2021)

Photogrammetric Coded Point Localization Based on Target Detection Network

Dahui Qin, Dong Cheng*, Mingzhu Su, Yunfei Duan, and Yongbo Shao
Author Affiliations
  • School of Civil Engineering and Geomatics, Southwest Petroleum University, Chengdu, Sichuan 610500, China
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    Figures & Tables(16)
    Coded markers. (a) Structure of coding; (b) scale of cross coding
    Detection flow of YOLO v3
    Bottleneck layer
    Transition layer
    Dense residual block
    Backbone network of improved YOLO v3
    False mark points
    Center positioning of coded points. (a) Target segmentation; (b) pretreatment; (c) centroid extraction; (d) center positioning
    Precision-Recall curves of model
    Comparison of detection effect of two experiments for the same photo. (a) Experiment 1; (b) experiment 1
    Test results in different environments
    Nearest distance comparison
    Influence of salt-and-pepper noise on recognition rate
    Influence of Gaussian noise on recognition rate
    Decoding results. (a) Poor condition; (b) good condition
    • Table 1. Detection results of two models

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      Table 1. Detection results of two models

      AlgorithmXTPXFPXFNPRAP /%
      YOLO v397817260.980.9687.86
      M-YOLO10089170.990.9894.91
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    Dahui Qin, Dong Cheng, Mingzhu Su, Yunfei Duan, Yongbo Shao. Photogrammetric Coded Point Localization Based on Target Detection Network[J]. Laser & Optoelectronics Progress, 2021, 58(4): 0410011

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    Paper Information

    Category: Image Processing

    Received: Jun. 28, 2020

    Accepted: Aug. 7, 2020

    Published Online: Feb. 8, 2021

    The Author Email: Cheng Dong (chengdong203@qq.com)

    DOI:10.3788/LOP202158.0410011

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