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Technology of Graphic & Image
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App. Res. of Comp. Printed Article
Vol. 39, 2022 No. 7
2196-2202

Gesture recognition algorithm combining attention and time-domain multiscale convolution

Mao Li
Zhang Yinan
Sun Jun
Jiangsu Provincial Engineering Laboratory of Pattern Recognition & Computational Intelligence, Jiangnan University, Wuxi Jiangsu 214122, China
DOI: 10.19734/j.issn.1001-3695.2021.11.0620

Abstract

In dynamic gesture recognition methods based on deep learning, aiming at the problems of large network scale, simple dimension of extracted spatiotemporal features, and insufficient extraction ability of effective features, this paper proposed a deep network framework. Firstly, this paper applied a novel spatiotemporal convolution module based on multiscale information fusion in the time domain to improve the 3D residual network structure, greatly reduced the size of the network and obtained rich spatiotemporal receptive field characteristics. Then it introduced a spatiotemporal feature channel attention mechanism with global information synchronization, and used a few parameters to construct the global dependency between feature maps, and the module could obtain the key features of dynamic gestures more efficiently. The experimental results on the self-built gesture dataset SHC and the public gesture dataset SKIG show that the proposed gesture recognition method has fewer parameters and more powerful multiscale spatiotemporal feature extraction ability, and gains a higher recognition rate than the current mainstream algorithms.

Foundation Support

国家重点研发计划资助项目(2017YFC1601800)
国家自然科学基金资助项目(61672263)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2021.11.0620
Publish at: Application Research of Computers Printed Article, Vol. 39, 2022 No. 7
Section: Technology of Graphic & Image
Pages: 2196-2202
Serial Number: 1001-3695(2022)07-045-2196-07

Publish History

[2022-01-18] Accepted Paper
[2022-07-05] Printed Article

Cite This Article

毛力, 张艺楠, 孙俊. 融合注意力与时域多尺度卷积的手势识别算法 [J]. 计算机应用研究, 2022, 39 (7): 2196-2202. (Mao Li, Zhang Yinan, Sun Jun. Gesture recognition algorithm combining attention and time-domain multiscale convolution [J]. Application Research of Computers, 2022, 39 (7): 2196-2202. )

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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