基于多传感器融合的动态手势识别研究分析  

Dynamic gesture recognition research and analysis based on multi-sensor fusion

作　　者：马正华[1] 李雷[2] 乔玉涛[2] 戎海龙 曹海婷 MA Zhenghua;LI Lei;QIAO Yutao;RONG Hailong;CAO Haiting(Graduate Division, Changzhou University, Changzhou, Jiangsu 213164, China;School of Information Science & Engineering, School of Mathematics & Physics, Changzhou University, Changzhou,Jiangsu 213164, China;School of Urban Rail Transit, Changzhou University, Changzhou, Jiangsu 213164, China)

机构地区：[1]常州大学研究生部,江苏常州213164 [2]常州大学信息科学与工程学院数理学院,江苏常州213164 [3]常州大学城市轨道交通学院,江苏常州213164

出　　处：《计算机工程与应用》2017年第17期153-159,共7页Computer Engineering and Applications

基　　金：国家自然科学基金(No.61201096);机器人技术与系统国家重点实验室开放基金重点资助项目(No.SKLRS-2010-2D-09;No.SKLRS-2010-MS-10);江苏省高校自然科学研究面上资助项目(No.10KJB510003);江苏省自然科学基金(No.BK20140265);常州市科技资助项目(No.CJ20110023;No.CM20123006)

摘　　要：研究利用三类传感器(表面肌电仪、陀螺仪和加速度计)信号的特点进行信息融合,提高可识别动态手势动作的种类和准确率。将动态手势动作分解为手形、手势朝向和运动轨迹三个要素,分别使用表面肌电信号(s EMG)、陀螺仪信号(GYRO)和加速度信号(ACC)进行表征,利用多流HMMs进行动态手势动作的模式识别。对包含有5个运动轨迹和6个静态手形的识别实验结果表明,该方法可以有效地从连续信号中识别动态手势,三类传感器组合使用获得的全局平均识别率达到92%以上,明显高于任意两个传感器组合和仅采用单个传感器获得的平均识别率。实验表明该方法是一种有效的动态手势识别方法,并且相较于传统的动态手势识别的方法更具有优势。This paper studies using three kinds of sensors(surface electromyography,gyroscope and accelerometer)singnal characteristics for information fusion.The purpose is to improve the types and accuracy of recognizable dynamic hand gestures.Dynamic hand gestures are divided into three elements:hand shape,gestures towards and trajectory.The three elements are respectively represented by surface Electromyogram signal(sEMG),Gyroscope signal(GYRO)and Acceleration signal(ACC).Multi-streaming HMMs are used for pattern recognition of dynamic hand gestures.In the recognition experiments that contain five motion trajectories and six static hand shapes,the results show that this method can effectively identify dynamic hand gestures from the continuous signals.The global average recognition rate obtained from the composite use of three kinds of sensors is higher than92%.It is significantly higher than the average recognition rate that obtained from the combination of any two sensors or single sensor only.Experimental results show that this method is an effective dynamic gesture recognition method.And compared with the traditional dynamic gesture recognition method,this method has more advantages.

关 键 词：手势识别 表面肌电信号(sEMG) 加速度信号(ACC) 陀螺仪信号(GYRO) 多流隐马尔可夫模型(MHMMs) 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术]