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Technology of Graphic & Image
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App. Res. of Comp. Printed Article
Vol. 41, 2024 No. 9
2867-2873

Action recognition algorithm based on global frequency domain pooling

Jia Zhichao1
Zhang Haichao1
Zhang Chuang1,2
Yan Mengmeng1
Chu Jinqi1
Yan Zhiyue1
1. College of Electronic & Information Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China
2. Jiangsu Key Laboratory of Meteorological Observation & Information Processing, Nanjing 210044, China
DOI: 10.19734/j.issn.1001-3695.2023.11.0596

Abstract

The current 3D-ConvNet-based action recognition algorithms generally use GAP to compress feature information. However, it leads to issues of information loss, redundancy, and network overfitting. To address these issues and enhance the retention of high-level semantic information extracted by the convolutional layer, this paper proposed an action recognition algorithm based on GFDP. Firstly, DCT shows that GAP is a special case of feature decomposition in the frequency domain. Therefore, the algorithm introduced more frequency components to increase the specificity between feature channels and reduce the information redundancy after information compression. Secondly, to better suppress the overfitting problem, the algorithm introduced the batch normalization strategy to the convolutional layer and extended it to the fully connected layer of the action recognition model with ERB-Res3D as the skeleton to optimize the data distribution. Finally, this paper verified the proposed method on the UCF101 dataset. The results reveals that the model's computational load is 3.5 GFlops, with 7.4 million parameters. The final recognition accuracy improved by 3.9% based on the ERB-Res3D model and 17.4% based on the original Res3D model. This improvement effectively achieves more accurate behavior recognition results.

Foundation Support

国家自然科学基金资助项目(62272234)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2023.11.0596
Publish at: Application Research of Computers Printed Article, Vol. 41, 2024 No. 9
Section: Technology of Graphic & Image
Pages: 2867-2873
Serial Number: 1001-3695(2024)09-042-2867-07

Publish History

[2024-02-23] Accepted Paper
[2024-09-05] Printed Article

Cite This Article

贾志超, 张海超, 张闯, 等. 基于全局频域池化的行为识别算法 [J]. 计算机应用研究, 2024, 41 (9): 2867-2873. (Jia Zhichao, Zhang Haichao, Zhang Chuang, et al. Action recognition algorithm based on global frequency domain pooling [J]. Application Research of Computers, 2024, 41 (9): 2867-2873. )

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.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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