Infrared and Laser Engineering, Volume. 52, Issue 8, 20230427(2023)

Advancements in fusion calibration technology of lidar and camera

Shiqiang Wang, Zhaozong Meng, Nan Gao, and Zonghua Zhang
Author Affiliations
  • School of Mechanical Engineering, Hebei University of Technology, Tianjin 300130, China
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    Figures & Tables(10)
    Camera model mapping process
    (a) Coordinate system of lidar; (b) Scanning range in the vertical direction (\begin{document}${\delta }_{\min}-{\delta }_{\max}$\end{document}); (c); Scanning parameters in the vertical plane; (d) Scanning parameters on the horizontal plane
    Calibration principle of lidar and camera
    Multi-source data fusion process
    The extrinsic calibration methods of lidar and camera
    (a) Checkerboard with border; (b) Checkerboard without border
    Non-checkerboard 2D calibration board
    • Table 1. Characteristics of different camera intrinsic calibration methods

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      Table 1. Characteristics of different camera intrinsic calibration methods

      Calibration methodStabilityAccuracyFlexibilitySpeedTarget
      Traditional methodsDLT[12]LLLHY
      Tasi[13]MHLMY
      Zhang[14]MHMMY
      Self-calibration methodsKruppa[15]MMHHN
      VP[16]LMHHN
      BA[17]LMHMN
      AVC[18]HHLLY
    • Table 2. Characteristics of different type lidar

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      Table 2. Characteristics of different type lidar

      No.TypeTechnologyAdvantageDisadvantage
      1Mechanical lidarSingle line scanning or multi-line scanningCircular scanning, large scanning field, mature technology Large volume, short life and high cost
      2Semi-solid state lidarMEMS methodSize miniaturization, low cost and high accuracySensitive to vibration, small field of vision
      3All-solid state lidar OPA methodSilicon-based scheme, low costThe technology is not mature and the application is few
      4Flash methodSmall size, 360° field of viewLow efficiency, immature technology
    • Table 3. Characteristics of different methods for lidar-camera extrinsic calibration

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      Table 3. Characteristics of different methods for lidar-camera extrinsic calibration

      Target featureMotionMutual informationDeep learning
      CharacteristicRequire targets, then calculate pnp based on featuresHand-eye calibration, the accuracy depends on motion estimation of the sensorsCorrelating image grayscale values with point reflectance, and specific applicationsextensive training and poor generalization
      AccuracyHLMM
      AutomaticityLMMH
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    Shiqiang Wang, Zhaozong Meng, Nan Gao, Zonghua Zhang. Advancements in fusion calibration technology of lidar and camera[J]. Infrared and Laser Engineering, 2023, 52(8): 20230427

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    Paper Information

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    Received: Jun. 15, 2023

    Accepted: --

    Published Online: Oct. 19, 2023

    The Author Email:

    DOI:10.3788/IRLA20230427

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