3D Reconstruction of Indoor Scenes Using RGB-D Monocular Vision

被引：1
|
作者：
Liu, Sanmao [1 ,2 ]
Zhu, Wenqiu [1 ,2 ]
Zhang, Canqing [1 ,2 ]
Sun, Wenjing [1 ,2 ]
机构：
[1] HuNan Univ Technol, Sch Comp & Commun, Zhu Zhou 412007, Peoples R China
[2] Key Lab Intelligent Informat Percept & Proc Techn, Zhuzhou 412007, Peoples R China
来源：
2016 INTERNATIONAL CONFERENCE ON ROBOTS & INTELLIGENT SYSTEM (ICRIS) | 2016年
关键词：
Monocular vision; Point cloud; 3D Reconstruction;
D O I：
10.1109/ICRIS.2016.116
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
Aiming at the problem of low speed of 3D reconstruction of indoor scenes with monocular vision, the color images and depth images of indoor scenes based on ASUS Xtion monocular vision sensor were used for 3D reconstruction. The image feature extraction using the ORB feature detection algorithm, and compared the efficiency of several kinds of classic feature detection algorithm in image matching, Ransac algorithm and ICP algorithm are used to point cloud fusion. Through experiments, a fast 3D reconstruction method for indoor, simple and small-scale static environment is realized. Have good accuracy, robustness, real-time and flexibility.
引用
收藏
页码：1 / 7
页数：7
相关论文
共 50 条
  • [1] 3D Reconstruction of Indoor Scenes using a Single RGB-D Image
    Bokaris, Panagiotis-Alexandros
    Muselet, Damien
    Tremeau, Alain
    [J]. PROCEEDINGS OF THE 12TH INTERNATIONAL JOINT CONFERENCE ON COMPUTER VISION, IMAGING AND COMPUTER GRAPHICS THEORY AND APPLICATIONS (VISIGRAPP 2017), VOL 6, 2017, : 394 - 401
  • [2] GeoRec: Geometry-enhanced semantic 3D reconstruction of RGB-D indoor scenes
    Huan, Linxi
    Zheng, Xianwei
    Gong, Jianya
    [J]. ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, 2022, 186 : 301 - 314
  • [3] A Survey of Indoor 3D Reconstruction Based on RGB-D Cameras
    Zhu, Jinlong
    Gao, Changbo
    Sun, Qiucheng
    Wang, Mingze
    Deng, Zhengkai
    [J]. IEEE ACCESS, 2024, 12 : 112742 - 112766
  • [4] Applications of RGB-D data for 3D reconstruction in the indoor environment
    Zou, Runyang
    Ge, Xueshi
    Wang, Geng
    [J]. 2016 IEEE CHINESE GUIDANCE, NAVIGATION AND CONTROL CONFERENCE (CGNCC), 2016, : 375 - 378
  • [5] Neural Colour Correction for Indoor 3D Reconstruction Using RGB-D Data
    Madeira, Tiago
    Oliveira, Miguel
    Dias, Paulo
    [J]. SENSORS, 2024, 24 (13)
  • [6] High Quality 3D Reconstruction of Indoor Finvironments using RGB-D Sensors
    Wang, Jun
    Huang, Shoudong
    Zhao, Liang
    Ge, Janet
    He, Sean
    Zhang, Chengqi
    Wang, Xiangyu
    [J]. PROCEEDINGS OF THE 2017 12TH IEEE CONFERENCE ON INDUSTRIAL ELECTRONICS AND APPLICATIONS (ICIEA), 2017, : 1739 - 1744
  • [7] Online Reconstruction of Indoor Scenes from RGB-D Streams
    Wang, Hao
    Wang, Jun
    Wang, Liang
    [J]. 2016 IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR), 2016, : 3271 - 3279
  • [8] Neural Surface Reconstruction of Dynamic Scenes with Monocular RGB-D Camera
    Cai, Hongrui
    Feng, Wanquan
    Feng, Xuetao
    Wang, Yan
    Zhang, Juyong
    [J]. ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 35 (NEURIPS 2022), 2022,
  • [9] Dense 3D Semantic Mapping of Indoor Scenes from RGB-D Images
    Hermans, Alexander
    Floros, Georgios
    Leibe, Bastian
    [J]. 2014 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA), 2014, : 2631 - 2638
  • [10] Semantic Segmentation Networks of 3D Point Clouds for RGB-D Indoor Scenes
    Wang, Ya
    Zell, Andreas
    [J]. TWELFTH INTERNATIONAL CONFERENCE ON MACHINE VISION (ICMV 2019), 2020, 11433
12345