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Technology of Graphic & Image
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3495-3501

Regional temporal changes learning for action recognition

Yang Xingming
Xu Hao
Wang Zhiwen
Gao Xujie
Wu Kewei
Xie Zhao
School of Computer Science & Information Engineering, Hefei University of Technology, Hefei 230601, China

Abstract

To solve the problem that existing action recognition methods lack the learning of regional-aware features in video frames, resulting in the confusion of similar action categories in the recognition process, this paper proposed a regional-aware temporal change network. This network included a local-global temporal feature learning module, a regional semantic learning module, and a regional semantic fusion module. The local-global temporal feature learning module learned local temporal attention to enhance video frame features and aggregated them into global temporal region features. The regional semantic learning module constructed changeable region semantic convolution kernels by computing the similarity between pixels in the region to learn action semantic features over time. The regional semantic fusion module took the changeable regional features and global temporal regional features as two independent branches and learned the channel attention of each branch separately for feature fusion. Experiments on the Something-Something V1&V2 and Kinetics-400 datasets show that the regional-aware temporal change network performs better than most action recognition methods, proving that the network can effectively improve the performance of action recognition.

Foundation Support

安徽省自然科学基金资助项目(2108085MF203)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2024.01.0013
Publish at: Application Research of Computers Printed Article, Vol. 41, 2024 No. 11
Section: Technology of Graphic & Image
Pages: 3495-3501
Serial Number: 1001-3695(2024)11-043-3495-07

Publish History

[2024-04-23] Accepted Paper
[2024-11-05] Printed Article

Cite This Article

杨兴明, 徐浩, 汪智文, 等. 区域时间变化学习的行为识别 [J]. 计算机应用研究, 2024, 41 (11): 3495-3501. (Yang Xingming, Xu Hao, Wang Zhiwen, et al. Regional temporal changes learning for action recognition [J]. Application Research of Computers, 2024, 41 (11): 3495-3501. )

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  • Application Research of Computers Monthly Journal
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    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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