Research of deep learning-based classification methods for 3D point cloud

Wei Tianqi
Zheng Xiongsheng
Zhejiang Ocean University, Zhoushan Zhejiang 316022, China

Abstract

With the rapid development of deep learning and 3D sensing technology, point cloud classification has been widely used in intelligent classification and other fields. In order to better promote the research and application of point cloud classification technology, this paper combed, analyzed and summarized the research progress of related methods systematically by using pipeline architecture. Firstly, according to the different point cloud data processing methods, it analyzed and summarized the existing point cloud classification methods into indirect point cloud based methods and direct point cloud based methods. Then, it introduced the representative methods and the latest research, compared and analyzed the core ideas, advantages and disadvantages, scope of application, application scenarios and experimental results of the main methods. Finally, it prospected the future development and research direction of point cloud classification from four aspects. The results show that 2D-3D feature fusion of indirect and direct point cloud methods is an important development direction in the future.

Foundation Support

舟山市科技计划项目(2021C21005)
浙江省科技厅尖兵领雁计划项目(2022C02001)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2021.10.0469
Publish at: Application Research of Computers Printed Article, Vol. 39, 2022 No. 5
Section: Survey
Pages: 1289-1296
Serial Number: 1001-3695(2022)05-002-1289-08

Publish History

[2021-12-29] Accepted Paper
[2022-05-05] Printed Article

Cite This Article

魏天琪, 郑雄胜. 基于深度学习的三维点云分类方法研究 [J]. 计算机应用研究, 2022, 39 (5): 1289-1296. (Wei Tianqi, Zheng Xiongsheng. Research of deep learning-based classification methods for 3D point cloud [J]. Application Research of Computers, 2022, 39 (5): 1289-1296. )

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  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

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