摘要
为了提高竞技武术套路中难度动作智能识别的准确性,以竞技武术套路中运动员动作的原始骨架数据建立运动员有向时空骨架图。在时空图卷积神经网络内,引入图注意力机制与通道注意力机制,建立基于注意力的时空图卷积神经网络。在该网络内输入运动员有向时空骨架图,输出难度动作智能识别结果。研究结果表明,所提识别方法可以准确提取难度动作的特征,对竞技武术套路中难度动作的识别精度较高。
In order to improve the accuracy of intelligent recognition of difficult movements in competitive martial arts routines,the directed space-time skeleton diagram of athletes is established based on the original skeleton data of athletes'movements in competitive martial arts routines.In the spatiotemporal graph convolutional neural network,the graph attention mechanism and channel attention mechanism are introduced to establish the spatiotemporal graph convolutional neural network based on attention.The spatial and temporal framework of athletes is input into the network,and the intelligent recognition result of the difficulty action is output.The research results show that the proposed recognition method can accurately extract the features of difficult movements,and the recognition accuracy of difficult movements in competitive martial arts routines is high,which is helpful for athletes to identify and improve difficult movements more accurately in training.
作者
陈威
葛士顺
CHEN Wei;GE Shishun(College of Physical Education,Huainan Normal University,Huainan 232001,China)
出处
《新乡学院学报》
2024年第6期72-76,共5页
Journal of Xinxiang University
基金
安徽省高校人文社会科学研究重点项目(SK2019A0567)。
关键词
竞技武术套路
难度动作
智能识别
competitive wushu routine
difficult movements
intelligent recognition
作者简介
陈威(1983-),男,安徽宿州人,讲师,硕士,研究方向:体育教学训练,竞技体育。
