Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/147247
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dc.contributor.authorZhang, Junen_US
dc.contributor.authorZhang, Ranen_US
dc.contributor.authorYue, Yufengen_US
dc.contributor.authorYang, Chuleen_US
dc.contributor.authorWen, Mingxingen_US
dc.contributor.authorWang, Danweien_US
dc.date.accessioned2021-03-29T05:11:17Z-
dc.date.available2021-03-29T05:11:17Z-
dc.date.issued2019-
dc.identifier.citationZhang, 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. https://dx.doi.org/10.1109/ROBIO49542.2019.8961462en_US
dc.identifier.isbn9781728163215-
dc.identifier.urihttps://hdl.handle.net/10356/147247-
dc.description.abstractAccurate 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.en_US
dc.language.isoenen_US
dc.rights© 2019 Institute of Electrical and Electronics Engineers (IEEE). All rights reserved.en_US
dc.subjectEngineeringen_US
dc.titleSLAT-Calib : extrinsic calibration between a sparse 3D LiDAR and a limited-FOV low-resolution thermal cameraen_US
dc.typeConference Paperen
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.contributor.conference2019 IEEE International Conference on Robotics and Biomimetics (ROBIO)en_US
dc.identifier.doi10.1109/ROBIO49542.2019.8961462-
dc.identifier.scopus2-s2.0-85079034952-
dc.identifier.spage648en_US
dc.identifier.epage653en_US
dc.subject.keywordsCalibrationen_US
dc.subject.keywordsImage Matchingen_US
dc.citation.conferencelocationDali, Chinaen_US
item.fulltextNo Fulltext-
item.grantfulltextnone-
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