Calibration Between Sparse LIDAR and Visible/Infrared Imaging Systems

LIU Yu; CAI Yi; RONG Ningtao; ZHOU Yunyang; WANG Lingxue

Volume 44 Issue 12

Dec. 2022

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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): 1264-1272.

Citation:

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): 1264-1272.

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): 1264-1272.

Citation:

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): 1264-1272.

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Calibration Between Sparse LIDAR and Visible/Infrared Imaging Systems

School of Optics and Photonics, MoE Key Laboratory of Photoelectronic Imaging Technology and System, Beijing Institute of Technology, Beijing 100081, China

Received Date: 2022-03-12
Rev Recd Date: 2022-04-19
Publish Date: 2022-12-20

Abstract

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.
- sparse LIDAR,
- pose estimation,
- calibration,
- calibration board,
- infrared imaging

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References(10)

References

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