• Infrared Technology
  • Vol. 44, Issue 12, 1264 (2022)
Yu LIU, Yi CAI, Ningtao RONG, Yunyang ZHOU, and Lingxue WANG
Author Affiliations
  • [in Chinese]
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    DOI: Cite this Article
    LIU Yu, CAI Yi, RONG Ningtao, ZHOU Yunyang, WANG Lingxue. Calibration Between Sparse LIDAR and Visible/Infrared Imaging Systems[J]. Infrared Technology, 2022, 44(12): 1264 Copy Citation Text show less

    Abstract

    Pose estimation between LIDAR and imaging system is the prerequisite for the data fusion. Among current mainstream off-line calibration methods, common checkerboard is generally effective for 64-line and above LIDAR, but not for 16-line LIDAR due to its sparse data and will lead to large error. Furthermore, when involving calibration of infrared imaging system, specially-made checkerboard is needed to produce difference of emissivity. Aiming at the problem of less information provided by sparse LIDARs, we propose a new calibration method that can jointly calibrate LIDAR and visible/infrared imaging systems. A novel diamond-shaped nine-hole calibration board is designed, and a geometric constraint loss function is proposed to optimize the coordinates of feature points. Finally, the infrared and visible light imaging systems are used respectively, to calibrate with 16-line LIDAR. Good results are achieved and show that, all the average reprojection error is within 3 pixels. The proposed method can also be used in calibration of multi-band imaging systems that include sparse LIDAR, visible imaging system and infrared imaging system.
    LIU Yu, CAI Yi, RONG Ningtao, ZHOU Yunyang, WANG Lingxue. Calibration Between Sparse LIDAR and Visible/Infrared Imaging Systems[J]. Infrared Technology, 2022, 44(12): 1264
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