Article: Design of action detection system in wrestling match video based on 3D convolutional neural network Journal: International Journal of Wireless and Mobile Computing (IJWMC) 2022 Vol.22 No.1 pp.29 - 37 Abstract: At present, there are some problems in motion detection in wrestling video at home and abroad, such as low detection accuracy and poor robustness. A motion detection system combining three-dimensional convolution neural network and recursive neural network is studied and designed. It uses three-dimensional convolution to obtain low-level feature code, then uses recursive memory module to obtain timing features, and finally completes motion detection according to timing features. Under the ratio of these three parameters, the accuracy of 3D-CNN convolutional neural network structure is higher than that of 2D-CNN. When the ratio of the influence factor of circular memory module P to that of circular memory module C is 1, the accuracy of 3D-CNN improves the fastest and the accuracy is close to 20%. The research results provide a new idea for the development of human motion detection and recognition technology. Inderscience Publishers - linking academia, business and industry through research

Title: Design of action detection system in wrestling match video based on 3D convolutional neural network

Authors: Yang Liu; Qinyu Mei; Xin Gan; Ya Zhu; Yongjie Wang

Addresses: Faculty of Table Tennis, Badminton and Tennis, Chengdu Sport University, Wuhou District, Sichuan, Chengdu, China ' School of Football, Chengdu Sport University, Wuhou District, Sichuan, Chengdu, China ' Faculty of Table Tennis, Badminton and Tennis, Chengdu Sport University, Wuhou District, Sichuan, Chengdu, China ' School of Wushu, Chengdu Sport University, Wuhou District, Sichuan, Chengdu, China ' Faculty of Table Tennis, Badminton and Tennis, Chengdu Sport University, Wuhou District, Sichuan, Chengdu, China

Abstract: At present, there are some problems in motion detection in wrestling video at home and abroad, such as low detection accuracy and poor robustness. A motion detection system combining three-dimensional convolution neural network and recursive neural network is studied and designed. It uses three-dimensional convolution to obtain low-level feature code, then uses recursive memory module to obtain timing features, and finally completes motion detection according to timing features. Under the ratio of these three parameters, the accuracy of 3D-CNN convolutional neural network structure is higher than that of 2D-CNN. When the ratio of the influence factor of circular memory module P to that of circular memory module C is 1, the accuracy of 3D-CNN improves the fastest and the accuracy is close to 20%. The research results provide a new idea for the development of human motion detection and recognition technology.

Keywords: 3D-CNN; three-dimensional convolutional neural network; action detection; wrestling video; spatio-temporal features.

DOI: 10.1504/IJWMC.2022.122483

International Journal of Wireless and Mobile Computing, 2022 Vol.22 No.1, pp.29 - 37

Received: 18 Sep 2021
Accepted: 22 Jan 2022
Published online: 27 Apr 2022 *

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Title: Design of action detection system in wrestling match video based on 3D convolutional neural network

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