Research on point-cloud collection and 3D model reconstruction

被引:0
作者
Sheng, Jianan [1 ]
Zhang, Jian [1 ]
Mi, Hong [2 ]
Ye, Maosheng [3 ]
机构
[1] Tongji Univ, Sch Mech Engn, Shanghai, Peoples R China
[2] LIANZHOU REFRIGERANTS CO LTD, Quzhou, Zhejiang, Peoples R China
[3] GAOMING ANNWA CERAM SANIT WARE CO LTD, Guangzhou, Peoples R China
来源
IECON 2020: THE 46TH ANNUAL CONFERENCE OF THE IEEE INDUSTRIAL ELECTRONICS SOCIETY | 2020年
基金
国家重点研发计划;
关键词
point-cloud collection; 3D model reconstruction; multi-line structured light; SHAPE; CALIBRATION;
D O I
10.1109/iecon43393.2020.9255086
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Point-cloud collection is used to collect 3D surface features from the object. 3D reconstruction can form a visual 3D model based on point- cloud. They are the important parts of 3D surface measurement. 3D surface measurement can effectively help enterprises shorten the design cycle, improve product quality, save labor costs, and improve the competitiveness of enterprises. Optical image measurement is a branch of 3D surface measurement. Because optical image measurement has the advantages of non-contact, high speed, high degree of automation and good flexibility, it has been researched and applied widely. Image processing and calibration technology are often used in optical image measurement. Image processing can extract valuable information from images, and calibration technology is necessary for mathematical model. Multi-line structured light has been widely used in the measurement.
引用
收藏
页码:5331 / 5336
页数:6
相关论文
共 50 条
  • [31] Virtual face reconstruction basing on skull 3D model
    Knyaz, VA
    Zheltov, SY
    Stepanyants, DG
    Saltykova, EB
    THREE-DIMENSIONAL IMAGE CAPTURE AND APPLICATIONS V, 2002, 4661 : 182 - 190
  • [32] PRA-Net: Point Relation-Aware Network for 3D Point Cloud Analysis
    Cheng, Silin
    Chen, Xiwu
    He, Xinwei
    Liu, Zhe
    Bai, Xiang
    IEEE TRANSACTIONS ON IMAGE PROCESSING, 2021, 30 : 4436 - 4448
  • [33] Multi-class point cloud completion networks for 3D cardiac anatomy reconstruction from cine magnetic resonance images
    Beetz, Marcel
    Banerjee, Abhirup
    Ossenberg-Engels, Julius
    Grau, Vicente
    MEDICAL IMAGE ANALYSIS, 2023, 90
  • [34] Research on 3D Reconstruction Method Based on Laser Rotation Scanning
    Liu, Tao
    Wang, Ningning
    Fu, Qiang
    Zhang, Yi
    Wang, Minghui
    2019 IEEE INTERNATIONAL CONFERENCE ON MECHATRONICS AND AUTOMATION (ICMA), 2019, : 1600 - 1604
  • [35] Research on 3D reconstruction method of cattle face based on image
    Weng, Zhi
    He, Dongchang
    Zheng, Yan
    Zheng, Zhiqiang
    Zhang, Yong
    Gong, Caili
    JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, 2023, 44 (06) : 10551 - 10563
  • [36] Context-Aware 3D Point Cloud Semantic Segmentation With Plane Guidance
    Weng, Tingyu
    Xiao, Jun
    Yan, Feilong
    Jiang, Haiyong
    IEEE TRANSACTIONS ON MULTIMEDIA, 2023, 25 : 6653 - 6664
  • [37] Leveraging Single-View Images for Unsupervised 3D Point Cloud Completion
    Wu, Lintai
    Zhang, Qijian
    Hou, Junhui
    Xu, Yong
    IEEE TRANSACTIONS ON MULTIMEDIA, 2025, 27 : 940 - 953
  • [38] 3D point cloud regularization method for uniform mesh generation of mining excavations
    Dabek, Przemyslaw
    Wodecki, Jacek
    Kujawa, Paulina
    Wroblewski, Adam
    Macek, Arkadiusz
    Zimroz, Radoslaw
    ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, 2024, 218 : 324 - 343
  • [39] 3D Point Cloud Analysis for Detection and Characterization of Defects on Airplane Exterior Surface
    Jovancevic, Igor
    Pham, Huy-Hieu
    Orteu, Jean-Jose
    Gilblas, Remi
    Harvent, Jacques
    Maurice, Xavier
    Brethes, Ludovic
    JOURNAL OF NONDESTRUCTIVE EVALUATION, 2017, 36 (04)
  • [40] PointMTL: Multi-Transform Learning for Effective 3D Point Cloud Representations
    Jian, Yifan
    Yang, Yuwei
    Chen, Zhi
    Qing, Xianguo
    Zhao, Yang
    He, Liang
    Chen, Xuekun
    Luo, Wei
    IEEE ACCESS, 2021, 9 (09): : 126241 - 126255