Multi-View Image-Based 3D Reconstruction in Indoor Scenes:A Survey

被引:0
|
作者
LU Ping [1 ,2 ]
SHI Wenzhe [1 ,2 ]
QIAO Xiuquan [3 ]
机构
[1] State Key Laboratory of Mobile Network and Mobile Multimedia Technology
[2] ZTE Corporation
[3] State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and
关键词
D O I
暂无
中图分类号
TP391.41 [];
学科分类号
080203 ;
摘要
Three-dimensional reconstruction technology plays an important role in indoor scenes by converting objects and structures in indoor environments into accurate 3D models using multi-view RGB images. It offers a wide range of applications in fields such as virtual reality, aug-mented reality, indoor navigation, and game development. Existing methods based on multi-view RGB images have made significant progress in 3D reconstruction. These image-based reconstruction methods not only possess good expressive power and generalization performance, but also handle complex geometric shapes and textures effectively. Despite facing challenges such as lighting variations, occlusion, and texture loss in in-door scenes, these challenges can be effectively addressed through deep neural networks, neural implicit surface representations, and other tech-niques. The technology of indoor 3D reconstruction based on multi-view RGB images has a promising future. It not only provides immersive and interactive virtual experiences but also brings convenience and innovation to indoor navigation, interior design, and virtual tours. As the technol-ogy evolves, these image-based reconstruction methods will be further improved to provide higher quality and more accurate solutions to indoor scene reconstruction.
引用
收藏
页码:91 / 98
页数:8
相关论文
共 50 条
  • [41] Hierarchical Denoising Method of Crop 3D Point Cloud Based on Multi-view Image Reconstruction
    Chen, Lei
    Yuan, Yuan
    Song, Shide
    COMPUTER AND COMPUTING TECHNOLOGIES IN AGRICULTURE XI, PT I, 2019, 545 : 416 - 427
  • [42] Image-based Fast 3D Reconstruction
    Xia, Jianjun
    Wang, Fei
    Zheng, Xiaocui
    PROCEEDINGS OF THE 2016 5TH INTERNATIONAL CONFERENCE ON MEASUREMENT, INSTRUMENTATION AND AUTOMATION (ICMIA 2016), 2016, 138 : 817 - 820
  • [43] Multi-View 3D Model Reconstruction Based on Multi-Level Perception
    Bai, Jing
    Xu, Hao
    Computer Engineering and Applications, 2024, 59 (02) : 232 - 239
  • [44] 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
  • [45] Adaptive Interaction-Based Multi-view 3D Object Reconstruction
    Miao, Jun
    Zheng, Yilin
    Yan, Jie
    Li, Lei
    Chu, Jun
    ARTIFICIAL NEURAL NETWORKS AND MACHINE LEARNING, ICANN 2023, PT II, 2023, 14255 : 51 - 64
  • [46] Multi-View Images 3D Reconstruction based on Spatial Geometric Constraint
    Liu, Haibo
    PROCEEDINGS OF THE 2016 2ND WORKSHOP ON ADVANCED RESEARCH AND TECHNOLOGY IN INDUSTRY APPLICATIONS, 2016, 81 : 1217 - 1220
  • [47] A review and comparison of multi-view 3D reconstruction methods
    Jadhav, Tushar
    Singh, Kulbir
    Abhyankar, Aditya
    JOURNAL OF ENGINEERING RESEARCH, 2017, 5 (03): : 50 - 72
  • [48] A Real World Dataset for Multi-view 3D Reconstruction
    Shrestha, Rakesh
    Hu, Siqi
    Gou, Minghao
    Liu, Ziyuan
    Tan, Ping
    COMPUTER VISION, ECCV 2022, PT VIII, 2022, 13668 : 56 - 73
  • [49] MVLayoutNet: 3D Layout Reconstruction with Multi-view Panoramas
    Hu, Zhihua
    Duan, Bo
    Zhang, Yanfeng
    Sun, Mingwei
    Huang, Jingwei
    PROCEEDINGS OF THE 30TH ACM INTERNATIONAL CONFERENCE ON MULTIMEDIA, MM 2022, 2022, : 1289 - 1298
  • [50] MULTI-VIEW 3D RECONSTRUCTION FROM VIDEO WITH TRANSFORMER
    Zhong, Yijie
    Sun, Zhengxing
    Sun, Yunhan
    Luo, Shoutong
    Wang, Yi
    Zhang, Wei
    2022 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, ICIP, 2022, : 1661 - 1665