Infrared and Laser Engineering, Volume. 49, Issue 6, 20200078(2020)

Euclidean 3D reconstruction based on structure from motion of matching adjacent images

Kan Wang1... Jun Gong2, Jinghe Wei3, Ce Zhu4 and Kai Liu1 |Show fewer author(s)
Author Affiliations
  • 1四川大学 电气工程学院,四川 成都 610065
  • 2成都市产品质量监督检验院,四川 成都 610199
  • 3中科芯集成电路有限公司,江苏 无锡 214072
  • 4电子科技大学 信息与通信工程学院,四川 成都 611731
  • show less

    Traditional incremental structure from motion is susceptible to scale change, and the reconstructed point cloud is hierarchical and has no units. A new Euclidean 3D reconstruction method was proposed by improving the reconstruction topology and the scaling iterative closest point algorithm. First, a new reconstruction topology, reconstructing a point cloud from two adjacent pictures and then merging it into the main point cloud, was presented; then, corresponding tables were established aiming to find the corresponding 3D point pairs of a world point between the newly created point cloud and the main point cloud; subsequently, combining Geman-McClure norm, an anti-noise scaling iterative closest point method was proposed; finally, ground control points were set up to introduce scale for the reconstructed point cloud. Experiment results show that the point cloud reconstructed by proposed method is more accurate than that reconstructed by traditional incremental structure from motion, and the absolute error of length for the point cloud is about 1%-2%. The proposed method is suitable for precise Euclidean reconstruction of objects in close scene.

    Tools

    Get Citation

    Copy Citation Text

    Kan Wang, Jun Gong, Jinghe Wei, Ce Zhu, Kai Liu. Euclidean 3D reconstruction based on structure from motion of matching adjacent images[J]. Infrared and Laser Engineering, 2020, 49(6): 20200078

    Download Citation

    EndNote(RIS)BibTexPlain Text
    Save article for my favorites
    Paper Information

    Category: Special issue-Optical 3D imaging and sensing

    Received: Mar. 1, 2020

    Accepted: --

    Published Online: Aug. 19, 2020

    The Author Email:

    DOI:10.3788/IRLA20200078

    Topics