Design of action detection system in wrestling match video based on 3D convolutional neural network Online publication date: Wed, 27-Apr-2022
by Yang Liu; Qinyu Mei; Xin Gan; Ya Zhu; Yongjie Wang
International Journal of Wireless and Mobile Computing (IJWMC), Vol. 22, No. 1, 2022
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.
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