Technology of Graphic & Image
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App. Res. of Comp. Printed Article
Vol. 39, 2022 No. 11
3498-3502,3508

Action recognition based on adaptive partition and association of key-frame nodes

Liu Suolan1,2
Tian Zhenzhen1
Gu Jiahui1
Zhou Yuejing1
1. School of Computer & Artificial Intelligence, Changzhou University, Changzhou Jiangshu 213164, China
2. Jiangsu Key Laboratory of Social Security Image & Video Understanding, Nanjing University of Science & Technology, Nanjing 210094, China
DOI: 10.19734/j.issn.1001-3695.2022.02.0123

Abstract

In the task of human behavior recognition, most of the video frames do not include important discrimination information, which seriously affects the accuracy of application. Key pose frames can effectively express the video and reduce the amount of computation. Furthermore, bone data contains richer information than RGB image. Therefore, this paper proposed an action recognition approach based on adaptive partition and association of key-frame nodes. Firstly, it constructed an adaptive pooled deep network to evaluate frames importance and obtain key pose sequence. Then, it established association between nodes in unnatural connection state by self-learning model. Finally, it applied the improved spatio-temporal information on STGCN and used softmax for classification. This paper evaluated the effectiveness of the proposed approach by comparing with several typical technologies on the open-source and large-scale datasets of NTU-RGB+D and Kinetics. Experimental results show that it can reduce the amount of redundant data and retain key action information, and obtain higher average accuracy by 0.63% ~ 11.81% than the compared methods.

Foundation Support

国家自然科学基金资助项目(61976028)
江苏省社会安全图像与视频理解重点实验室课题(J2021-2)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2022.02.0123
Publish at: Application Research of Computers Printed Article, Vol. 39, 2022 No. 11
Section: Technology of Graphic & Image
Pages: 3498-3502,3508
Serial Number: 1001-3695(2022)11-049-3498-05

Publish History

[2022-05-24] Accepted Paper
[2022-11-05] Printed Article

Cite This Article

刘锁兰, 田珍珍, 顾嘉晖, 等. 基于关键帧节点自适应分区与关联的行为识别算法 [J]. 计算机应用研究, 2022, 39 (11): 3498-3502,3508. (Liu Suolan, Tian Zhenzhen, Gu Jiahui, et al. Action recognition based on adaptive partition and association of key-frame nodes [J]. Application Research of Computers, 2022, 39 (11): 3498-3502,3508. )

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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