Research on Multi-View 3D Reconstruction Technology Based on SFM

被引:21
|
作者
Gao, Lei [1 ]
Zhao, Yingbao [1 ]
Han, Jingchang [1 ]
Liu, Huixian [1 ]
机构
[1] Hebei Univ Sci & Technol, Sch Elect Engn, Shijiazhuang 050018, Hebei, Peoples R China
关键词
multi-view 3D reconstruction; feature-point detection and matching; sparse reconstruction; a dense reconstruction;
D O I
10.3390/s22124366
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
Multi-view 3D reconstruction technology is used to restore a 3D model of practical value or required objects from a group of images. This paper designs and implements a set of multi-view 3D reconstruction technology, adopts the fusion method of SIFT and SURF feature-point extraction results, increases the number of feature points, adds proportional constraints to improve the robustness of feature-point matching, and uses RANSAC to eliminate false matching. In the sparse reconstruction stage, the traditional incremental SFM algorithm takes a long time, but the accuracy is high; the traditional global SFM algorithm is fast, but its accuracy is low; aiming at the disadvantages of traditional SFM algorithm, this paper proposes a hybrid SFM algorithm, which avoids the problem of the long time consumption of incremental SFM and the problem of the low precision and poor robustness of global SFM; finally, the MVS algorithm of depth-map fusion is used to complete the dense reconstruction of objects, and the related algorithms are used to complete the surface reconstruction, which makes the reconstruction model more realistic.
引用
收藏
页数:17
相关论文
共 50 条
  • [1] Research on Multi-view 3D Reconstruction of Human Motion Based on OpenPose
    Li, Xuhui
    Cai, Cheng
    Zhou, Hengyi
    COGNITIVE COMPUTING, ICCC 2021, 2022, 12992 : 72 - 78
  • [2] Overview of 3D Reconstruction Methods Based on Multi-view
    Li, Mengxin
    Zheng, Dai
    Zhang, Rui
    Yin, Jiadi
    Tian, Xiangqian
    2015 7TH INTERNATIONAL CONFERENCE ON INTELLIGENT HUMAN-MACHINE SYSTEMS AND CYBERNETICS IHMSC 2015, VOL II, 2015,
  • [3] Underwater 3D reconstruction based on multi-view stereo
    Gu, Feifei
    Zhao, Juan
    Xu, Pei
    Huang, Shulan
    Zhang, Gaopeng
    Song, Zhan
    OCEAN OPTICS AND INFORMATION TECHNOLOGY, 2018, 10850
  • [4] 3D Reconstruction for Multi-view Objects
    Yu, Jun
    Yin, Wenbin
    Hu, Zhiyi
    Liu, Yabin
    COMPUTERS & ELECTRICAL ENGINEERING, 2023, 106
  • [5] Multi-view 3D Reconstruction with Transformers
    Wang, Dan
    Cui, Xinrui
    Chen, Xun
    Zou, Zhengxia
    Shi, Tianyang
    Salcudean, Septimiu
    Wang, Z. Jane
    Ward, Rabab
    2021 IEEE/CVF INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV 2021), 2021, : 5702 - 5711
  • [6] Research on automatic 3D reconstruction of plant phenotype based on Multi-View images
    Yang, Danni
    Yang, Huijun
    Liu, Dongfeng
    Wang, Xianlin
    COMPUTERS AND ELECTRONICS IN AGRICULTURE, 2024, 220
  • [7] Unsupervised 3D reconstruction method based on multi-view propagation
    Luo J.
    Yuan D.
    Zhang L.
    Qu Y.
    Su S.
    Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University, 2024, 42 (01): : 129 - 137
  • [8] FLAME-Based Multi-view 3D Face Reconstruction
    Zheng, Wenzhuo
    Zhao, Junhao
    Liu, Xiaohong
    Pan, Yongyang
    Gan, Zhenghao
    Han, Haozhe
    Liu, Ning
    ADVANCES IN COMPUTER GRAPHICS, CGI 2023, PT IV, 2024, 14498 : 327 - 339
  • [9] 3D Face Reconstruction based on Multi-View Stereo Algorithm
    Peng, Keju
    Guan, Tao
    Xu, Chao
    Zhou, Dongxiang
    2014 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND BIOMIMETICS IEEE-ROBIO 2014, 2014, : 2310 - 2314
  • [10] 3D Texture Mapping in Multi-view Reconstruction
    Chen, Zhaolin
    Zhou, Jun
    Chen, Yisong
    Wang, Guoping
    ADVANCES IN VISUAL COMPUTING, ISVC 2012, PT I, 2012, 7431 : 359 - 371