桂林电子科技大学学报2026，Vol.46Issue(1)：59-66,8.DOI:10.16725/j.1673-808X.202448
基于Kinect和改进DTW的交通指挥手势识别方法
Traffic command gesture recognition method based on Kinect and improved DTW
摘要
Abstract
With the rapid development of autonomous driving technology,how to accurately and quickly recognize traffic command gestures has become an emerging traffic safety technical problem.Kinect is used to extract human skeleton data,and according to the characteristics of traffic gestures,bone angle features and the joint distance features are extracted and compared for analysis.The dynamic time warping(DTW)algorithm is combined with the Kinect for gesture recognition.Aiming at the path singularity prob-lem of DTW algorithm,the shape feature and numerical feature of the sequence are used to improve the DTW algorithm.Mean-while,considering the influence of unknown actions outside the boundary,an action discrimination method based on the correlation coefficient of matching distance sequence waveforms is proposed.The experimental results show that in terms of traffic command gesture recognition,the recognition accuracy of bone angle features is better than that of joint distance features,and the improved DTW algorithm has higher recognition accuracy than the DTW algorithm and LSTM network,and exhibits better generalization than the DTW algorithm.关键词
手势识别/Kinect/骨骼信息/交通指挥手势/动态时间规整算法Key words
gesture recognition/Kinect/skeleton data/traffic command gesture/dynamic time warping algorithm分类
信息技术与安全科学引用本文复制引用
陈启博,闫坤,陈杰伟,章芮宁,刘兴..基于Kinect和改进DTW的交通指挥手势识别方法[J].桂林电子科技大学学报,2026,46(1):59-66,8.基金项目
国家自然科学基金(62101147) （62101147）
广西自然科学基金(2020GXNSFAA159146) （2020GXNSFAA159146）
广西创新驱动发展专项(AA21077008) （AA21077008）
认知无线电与信息处理教育部重点实验室基金(CRKL190108) （CRKL190108）
