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Title: SLAT-Calib : extrinsic calibration between a sparse 3D LiDAR and a limited-FOV low-resolution thermal camera
Authors: Zhang, Jun
Zhang, Ran
Yue, Yufeng
Yang, Chule
Wen, Mingxing
Wang, Danwei
Keywords: Engineering
Issue Date: 2019
Source: Zhang, J., Zhang, R., Yue, Y., Yang, C., Wen, M. & Wang, D. (2019). SLAT-Calib : extrinsic calibration between a sparse 3D LiDAR and a limited-FOV low-resolution thermal camera. 2019 IEEE International Conference on Robotics and Biomimetics (ROBIO), 648-653.
metadata.dc.contributor.conference: 2019 IEEE International Conference on Robotics and Biomimetics (ROBIO)
Abstract: Accurate estimation of extrinsic parameter (rotation matrix and translation vector) between heterogeneous sensors is important for fusing complementary information. However, the extrinsic calibration between a sparse 3D LiDAR and a thermal camera is challenging, mainly because of the difficulties to accurately extract common features from a sparse point cloud and a thermal image which has limited-FOV and low-resolution. Previous methods either rely on a dense depth sensor or a visual camera to facilitate the feature extraction process. To address the problem, SLAT-Calib (Sparse Lidar And Thermal camera Calibration) is proposed. By observing that circular holes could be detected from both sensors, a specially designed calibration board (a rectangular board with four circular holes) is introduced. Four circle centers in 3D space are used as common features. The benefit is point features are accurate and reliable for feature matching. To extract four circle centers from the thermal camera, three steps are carried out: First, a method is proposed to accurately detect the four circles. Then, the homography matrix of the calibration board can be figured out. Lastly, 3D coordinates of the circle centers are calculated by decomposing the homography matrix. From the LiDAR frame, the four circle centers can be segmented out as long as two laser beams pass through each circle. At last, optimal extrinsic parameter is calculated by minimizing the matching error between the four pairs of 3D circle centers. Quantitative and qualitative experiments are carried out. In simulation, SLAT-Calib outperforms two methods by a large margin. In real environment, it achieves a re-projection error (RMSE) of 0.62 pixel.
ISBN: 9781728163215
DOI: 10.1109/ROBIO49542.2019.8961462
Schools: School of Electrical and Electronic Engineering 
Rights: © 2019 Institute of Electrical and Electronics Engineers (IEEE). All rights reserved.
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:EEE Conference Papers

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