Review of human action recognition based on improved deep learning methods

Zhu Xianghua
Zhi Min
College of Computer Science & Technology, Inner Mongolia Normal University, Hohhot 010022, China

Abstract

In order to sort out the development of deep learning methods in the field of human action recognition, this paper summarized the most representative models and algorithms in this field in recent years. Firstly, it described in detail the latest achievements, advantages and disadvantages and network structure of deep learning methods in video pre-processing stage based on the task flow of human action recognition. Then, it introduced two kinds of datasets related to human action recognition. Finally, it discussed and prospected the future research direction of human action recognition.

Foundation Support

内蒙古自治区高等学校科学研究资助项目(NJZZ21004)
内蒙古自然科学基金资助项目(2018MS06008)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2021.07.0296
Publish at: Application Research of Computers Printed Article, Vol. 39, 2022 No. 2
Section: Survey
Pages: 342-348
Serial Number: 1001-3695(2022)02-003-0342-07

Publish History

[2021-10-18] Accepted Paper
[2022-02-05] Printed Article

Cite This Article

朱相华, 智敏. 基于改进深度学习方法的人体动作识别综述 [J]. 计算机应用研究, 2022, 39 (2): 342-348. (Zhu Xianghua, Zhi Min. Review of human action recognition based on improved deep learning methods [J]. Application Research of Computers, 2022, 39 (2): 342-348. )

About the Journal

  • 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.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

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