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赵鹏程
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Personal Information
  • Supervisor of Master's Candidates
  • Name (Pinyin):Zhao Pengcheng
  • Date of Birth:1993-09-05
  • E-Mail:
  • Date of Employment:2019-12-07
  • Administrative Position:高级实验师
  • Education Level:With Certificate of Graduation for Doctorate Study
  • Business Address:武汉大学信息学部遥感信息工程学院（5号楼）315办公室
  • Gender:Male
  • Contact Information:+86 15972003670
  • Status:Employed
  • Alma Mater:武汉大学
  • Teacher College:School of Remote Sensing and Information Engineering
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Paper Publications
Current position: Home   >   Scientific Research   >   Paper Publications

Research on Coloring of 3D Point Cloud and Panoramic Image Based on Handheld SLAM

  • Date of Publication:2025-01-07
  • Hits:

  • DOI number: 

    10.1109/geoinformatics57846.2022.9963818

  • Affiliation of Author(s): 

    School of Remote Sensing and Information Engineering, Wuhan University, China

  • Journal: 

    International Conference on Geoinformatics

  • Key Words: 

    Data fusion,Imaging systems,Indoor positioning systems,3D point cloud,Cloud image,Handhelds,Handhold mobile scanning system,Panoramic images,Point-clouds,Position and orientations,Registration,Scanning systems,Simultaneous localization and mapping,Robotics,Handheld mobile scanning system,panoramic image,point cloud,registration,SLAM

  • Abstract: 

    Handheld mobile scanning systems usually do not integrate high-precision position and orientation system (POS), and the traditional 3D point cloud and 2D image coloring lack a unified spatial reference. This letter proposes a method for registration and coloring of 3D point cloud and panoramic image obtained by handheld simultaneous localization and mapping (SLAM) system. Firstly, the initial registration parameters are generated by slam trajectory coordinate and pose interpolation. Secondly, the point cloud is converted into depth map according to the spherical 3D-2D imaging model, and then the optimal registration parameters between depth map and panorama are calculated based on the mutual information maximization. Finally, the multi segment point cloud is colored in batch by using optimal parameters, generating the color point cloud of the complete scene. The experimental results show that our method can realize the coloring of point clouds in different scenes such as indoor and outdoor without POS, and is suitable for the data fusion application of handheld scanning point clouds and panoramic images. © 2022 IEEE.

  • Co-author: 

    Li, Pengcheng,Zhao, Qingwu,Hu, Shaocong

  • Indexed by: 

    会议论文

  • Discipline: 

    Engineering

  • Document Type: 

    C

  • Volume: 

    2022-August

  • ISSN No.: 

    2161-024X

  • Translation or Not: 

    no

  • CN No.: 

    Scopus:2-s2.0-85143886204,EI:20225113258628

  • Date of Publication: 

    2022-08-15

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