摘要
针对当前识别摆臂动作方法中直接提取图像特征,导致摆臂动作识别结果与实际摆臂动作运动轨迹拟合度较低的问题,提出基于多尺度细节增强的短跑训练摆臂动作识别方法。利用图像多尺度分解、图像纹理细节增强、图像信息融合3个步骤凸显摆臂动作特征,通过训练摆臂动作多尺度细节图像特征,识别短跑训练摆臂动作。实验结果表明,该方法识别的运动轨迹与设置的实际摆臂动作运动轨迹拟合度偏差较小,摆臂动作识别效果较好。
There are problems in the method of arm swing action recognition that the image features are directly extracted,resulting in the low fit of the arm action recognition result and the actual arm movement trajectory.The method of the arm swing action recognition in sprint training based on multi-scale detail enhancement is proposed.The three steps of image multi-scale decomposition,image texture detail enhancement and image information fusion are used to highlight the action characteristics of the swing arm and identify the arm swing in sprint training.The experiment results show that the deviation of trajectory identified by this method and the actual trajectory of the swing arm is small,which has a better recognition effect of the arm swing.
作者
姜龙
朱继红
吴彬胜
JIANG Long;ZHU Jihong;WU Binsheng(Department of Public Sports,Lianyungang Technical College,Lianyungang 222006,China)
出处
《河南财政金融学院学报（自然科学版）》
2024年第3期66-72,共7页
Journal of Henan Finance University(Natural Science Edition)
基金
江苏省教育科学“十三五”规划重点资助课题(B-A20180328)。
关键词
摆臂动作
动作识别
短跑训练
多尺度细节增强
LSTM网络
swing arm action
action recognition
sprint training
multiscale detail enhancement
LSTM network
