Laser & Optoelectronics Progress, Volume. 61, Issue 14, 1428007(2024)

Research on Infrared and LiDAR Calibration Algorithm for Road Scene

Zhaofei Xu1,3, Jian Liao2、*, Hongcheng Wang1, Chong Kang2, Wei He1, and Wuyue Wang2
Author Affiliations
  • 1Yantai IRay Technology Co., Ltd., Yantai 264000, Shandong, China
  • 2Yantai Research Institute, Harbin Engineering University, Yantai 265503, Shandong, China
  • 3College of Mechanical and Electrical Engineering, Harbin Engineering University, Harbin 150006, Heilongjiang, China
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    Figures & Tables(19)
    Registration flow chart
    Infrared camera and LiDAR hardware synchronization solution
    Coordinate system diagram
    Sensor mounting location dimensions
    Lidar coordinate system translation
    LiDAR coordinate system rotation
    Coarse registration effect
    Coarse calibration effect test
    Principle of fine calibration
    Point cloud distribution of zebra line and lane line
    Comparison of zebra line point cloud extraction effects. (a) Zebra lines extracted by initial intensity threshold; (b) zebra lines extracted by adaptive intensity threshold
    Comparison of extraction effects of road pole point cloud. (a) Point cloud of road poles extracted using voxel columns; (b) point cloud of road poles extracted using voxel columns plus cylindrical fitting
    Comparison of pedestrian projection effects. (a) Coarse calibration projection effect; (b) fine calibration projection effect
    Calibration algorithm flow chart
    Comparison of alignment projection effect of different schemes. (a) Alignment effect of visible light and LiDAR; (b) alignment effect of infrared camera and LiDAR using visible light scheme; (c) alignment effect of proposed infrared camera and LiDAR
    Comparison of registration projection effects. (a) Visible light registration effect in foggy weather; (b) infrared registration effect in foggy weather; (c) night visible light registration effect; (d) night infrared registration effect
    • Table 1. Comparison of two types of time synchronization errors

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      Table 1. Comparison of two types of time synchronization errors

      Synchronization methodActual error /msTheoretical error /ms
      Software synchronization5.5<17
      Hardware synchronization2.42‒3
    • Table 2. Comparison of point cloud projection success rate

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      Table 2. Comparison of point cloud projection success rate

      Lateral distance

      Pedestrian longitudinal distance

      60 m

      Small vehicle longitudinal distance

      30 m

      Small vehicle longitudinal distance

      60 m

      Small vehicle longitudinal distance

      90 m

      Coarse calibrationFine calibrationCoarse calibrationFine calibrationCoarse calibrationFine calibrationCoarse calibrationFine calibration
      Lateral distance ±0 m60.0010080.9510048.3996.0057.1496.86
      Lateral distance ±5 m69.2310069.0310040.0095.4572.7395.87
      Lateral distance ±10 m096.2344.9094.9655.2192.2883.3395.00
      Lateral distance

      Large vehicle longitudinal distance

      40 m

      Large vehicle longitudinal distance

      80 m

      Large vehicle longitudinal distance

      120 m

      Coarse calibrationFine calibrationCoarse calibrationFine calibrationCoarse calibrationFine calibration
      Lateral distance ±0 m88.4410092.4510066.67100
      Lateral distance ±5 m84.8799.1259.2210055.5694.00
      Lateral distance ±10 m53.0996.0058.6798.0041.9491.20
    • Table 3. Comparison of point cloud projection ratios of existing programs

      View table

      Table 3. Comparison of point cloud projection ratios of existing programs

      Calibration methodologyNumber of extracted pointsNumber of successfully projected pointsProjection success ratio /%
      Checkerboard calibration methodology362466.67
      Proposed3636100
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    Zhaofei Xu, Jian Liao, Hongcheng Wang, Chong Kang, Wei He, Wuyue Wang. Research on Infrared and LiDAR Calibration Algorithm for Road Scene[J]. Laser & Optoelectronics Progress, 2024, 61(14): 1428007

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    Paper Information

    Category: Remote Sensing and Sensors

    Received: Nov. 1, 2023

    Accepted: Dec. 21, 2023

    Published Online: Jul. 11, 2024

    The Author Email: Liao Jian (liaojian0911@163.com)

    DOI:10.3788/LOP232408

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