• Laser & Optoelectronics Progress
  • Vol. 57, Issue 3, 030102 (2020)
Shaojie Chen1、2、*, Zhencai Zhu3, Yonghe Zhang1, Ming Guo1、**, and Shuai Zhi1、***
Author Affiliations
  • 1Innovation Academy for Microsatellite, Chinese Academy of Sciences, Shanghai 201203, China
  • 2University of Chinese Academy of Sciences, Beijing 100049, China
  • 3Innovation Academy for Microsatellites of CAS Key Laboratory, Shanghai 201203, China
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    DOI: 10.3788/LOP57.030102 Cite this Article Set citation alerts
    Shaojie Chen, Zhencai Zhu, Yonghe Zhang, Ming Guo, Shuai Zhi. Extrinsic Calibration for Lidar and Stereo Vision Using 3D Feature Points[J]. Laser & Optoelectronics Progress, 2020, 57(3): 030102 Copy Citation Text show less
    SGBM algorithm framework
    Fig. 1. SGBM algorithm framework
    Imaging system. (a) Geometric relationship between parallax and depth; (b) getting spatial points from pixel coordinates
    Fig. 2. Imaging system. (a) Geometric relationship between parallax and depth; (b) getting spatial points from pixel coordinates
    Experimental device diagram. (a) Board layout; (b) layout of lidar and binocular camera
    Fig. 3. Experimental device diagram. (a) Board layout; (b) layout of lidar and binocular camera
    Edge extraction. (a) (b) Edge extraction results of different perspectives of binocular camera; (c) frame selection of lidar point cloud
    Fig. 4. Edge extraction. (a) (b) Edge extraction results of different perspectives of binocular camera; (c) frame selection of lidar point cloud
    Point cloud fusion results from different perspectives in two scenes. (a) (b) Scene one; (c)(d) scene two
    Fig. 5. Point cloud fusion results from different perspectives in two scenes. (a) (b) Scene one; (c)(d) scene two
    Results of lidar point cloud reprojection
    Fig. 6. Results of lidar point cloud reprojection
    Point cloud fusion of two different perspectives of binocular camera. (a)(b) Left view of two perspectives; (c) result of the point cloud fusion
    Fig. 7. Point cloud fusion of two different perspectives of binocular camera. (a)(b) Left view of two perspectives; (c) result of the point cloud fusion
    Fusion results of method in Ref. [4]. (a) Result of edge point extraction; (b) result of circle center extraction
    Fig. 8. Fusion results of method in Ref. [4]. (a) Result of edge point extraction; (b) result of circle center extraction
    Fusion results of method in Ref. [4]. (a) Result 1; (b) another result
    Fig. 9. Fusion results of method in Ref. [4]. (a) Result 1; (b) another result
    Shaojie Chen, Zhencai Zhu, Yonghe Zhang, Ming Guo, Shuai Zhi. Extrinsic Calibration for Lidar and Stereo Vision Using 3D Feature Points[J]. Laser & Optoelectronics Progress, 2020, 57(3): 030102
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