Survey on Large Scale 3D Point Cloud Processing Using Deep Learning
Author:
Affiliation:

Clc Number:

Fund Project:

  • Article
  • |
  • Figures
  • |
  • Metrics
  • |
  • Reference
  • |
  • Related
  • |
  • Cited by
  • |
  • Materials
  • |
  • Comments
    Abstract:

    With the rapid development of 3D vision, large-scale 3D point cloud processing in real time based on deep learning has become a research hotspot. Taking a large-scale 3D point cloud with disordered spatial distribution as the background, this study comprehensively analyzes, introduces and compares the latest progress of deep learning in real-time processing of 3D vision problems. Then, it analyzes in detail and compares the advantages and disadvantages of algorithms in terms of point cloud segmentation, shape classification and target detection. Further, it briefly introduces the common data sets of point clouds and compares the algorithm performance of different data sets. Finally, the study points out the future research direction of 3D point cloud processing based on deep learning.

    Reference
    Related
    Cited by
Get Citation

王振燕,孙红岩,孙晓鹏.基于深度学习的大规模三维点云处理综述.计算机系统应用,2023,32(2):1-12

Copy
Share
Article Metrics
  • Abstract:
  • PDF:
  • HTML:
  • Cited by:
History
  • Received:January 15,2022
  • Revised:February 17,2022
  • Adopted:
  • Online: November 14,2022
  • Published:
You are the firstVisitors
Copyright: Institute of Software, Chinese Academy of Sciences Beijing ICP No. 05046678-3
Address:4# South Fourth Street, Zhongguancun,Haidian, Beijing,Postal Code:100190
Phone:010-62661041 Fax: Email:csa (a) iscas.ac.cn
Technical Support:Beijing Qinyun Technology Development Co., Ltd.

Beijing Public Network Security No. 11040202500063