• Laser & Optoelectronics Progress
  • Vol. 60, Issue 6, 0628010 (2023)
Jia Zhang1, Yi Tang1、*, Ziyu Bian2, Tianyu Sun1, and Kaijie Zhong2
Author Affiliations
  • 1Key Laboratory of Photoelectronic Imaging Technology and System, Ministry of Education, School of Optics and Photonics, Beijing Institute of Technology, Beijing 100081, China
  • 2Longrays Photoelectric Technology in Suzhou Co., Ltd., Suzhou 215300, Jiangsu , China
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    DOI: 10.3788/LOP220566 Cite this Article Set citation alerts
    Jia Zhang, Yi Tang, Ziyu Bian, Tianyu Sun, Kaijie Zhong. Fusion and Visualization of Three-Dimensional Point Cloud and Optical Images[J]. Laser & Optoelectronics Progress, 2023, 60(6): 0628010 Copy Citation Text show less

    Abstract

    Due to the lack of color information of three-dimensional point cloud and spatial information of optical images, a fusion method based on lidar and camera automatic calibration is proposed in this work. The fused data contains both the spatial information of the point cloud and color texture information of the optical images. First, the planar calibration plate was used to automatically calibrate the lidar and optical camera in steps. Second, the coordinate relationship was established through a collinear equation, and the color texture information of the optical image is given to the point cloud for fusion and visualization. The experimental results show that the fusion accuracy and the level of automation of the proposed method are improved. Compared to the calibration fusion method based on manual matching, the accuracy of the proposed method is improved by 51.7%. Compared to the calibration fusion method based on a trapezoidal checkerboard calibration board, the accuracy of the proposed method is improved by 36.4%. Considering the visualization results from multiple angles, the proposed method can better restore the color and spatial effects of real scenes.
    Jia Zhang, Yi Tang, Ziyu Bian, Tianyu Sun, Kaijie Zhong. Fusion and Visualization of Three-Dimensional Point Cloud and Optical Images[J]. Laser & Optoelectronics Progress, 2023, 60(6): 0628010
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