一种信道状态信息下的复杂动态手势识别方法

传统动态手势识别方法中存在硬件成本高,推广难度大等局限性.文章提出一种基于信道状态信息的复杂动态手势识别方法CSI-Num,该方法可用来实现对空中数字手势的高效识别.CSI-Num识别过程主要分为两个阶段:数据提取处理阶段与手势匹配识别阶段.提取处理阶段,是将采集到的数据,选取能够反映手势动作的子载波特征值作为被选信号,通过小波阈值函数和五点三次平滑方法对信号进行降噪平滑;匹配识别阶段,提取有效手势数据,使用k均值聚类算法和动态时间规整算法特性相融合的K-DTW匹配算法识别出不同数字的手势动作.实验结果表明,针对不同环境的室内场景,相应地调整参数设置,CSI-Num可以高效地识别出不同数字的手势动作,且具有较高鲁棒性.

Complex Dynamic Gesture Recognition Method Based on Channel State Information

The traditional dynamic gesture recognition method has some limitations,such as high hardware cost and difficulty in popularizing.The paper proposes a complex dynamic gesture recognition method CSI-Num,based on channel state information,which can realize the efficient recognition of digital gestures in the air.The process of CSI-Num recognition consists of two stages:data extraction processing and gesture matching recognition.In the stage of extracting and processing,the acquired data is selected as the selected signal,and by wavelet threshold function and five-spot triple smoothing method make the signal de-noised and smooth.In the phase of matching recognition,the valid gesture data is extracted,and using the K-DTW matching algorithm(combined k-means clustering algorithm and the characteristics of Dynamic Time Warping)can recognize the gesture actions with different numbers.The experimental results showthat CSI-Num can efficiently recognize different digital gestures and is robust to different indoor scenes and adjust the parameters accordingly.