Research on Key Technologies of RFID based Device Free Gesture Recognition
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摘要: 近年来手势识别作为人机交互的重要组成部分，受到广泛的关注.很多应用受益于手势识别，比如智能手机、智能家居、体感游戏等.与现有基于射频识别(radio frequency identification, RFID)的手势识别系统相比，基于RFID的免携带设备(device free)手势识别方法，不需要用户携带任何设备，因此有更好的用户体验.其主要思想是利用手势动作对信号的干扰信息作为指纹特征，并且利用多径增加匹配难度，从而保证了手势识别的准确度.具体思路为：通过数据分片解决RFID通信在时域上不连续的问题，进而采用雷达中合成孔径雷达(synthetic aperture radar, SAR)算法获取每个手势对应的指纹特征矩阵.最后，借鉴动态时间归整(dynamic time warping, DTW)算法匹配先验手势指纹库，从而完成手势识别.真实环境下的实验结果显示该方法可达到约85%的正确识别率，证明给出方法具有很高的可行性.Abstract: As a vital component of human-computer interaction, gesture recognition has gained a lot of attentions in civilian applications recently. Many applications would benefit from such gesture recognition, e.g. smart phone, smart home system, Kinect, etc. In this work, we introduce an RFID (radio frequency identification) based solution to recognize gestures using COTS (commercial off-the-shelf) RFID tags and readers. The basic idea is treating signal features caused by perturbation of gestures as the fingerprint. Furthermore, we leverage multipath to increase the difficulty of matching, which provides a high recognition rate. Unlike past work, which required user to attach an RFID tag, our method does not require any device to be attached to users. Specifically, we solve the problem that RFID communication is discontinuous in time domain by data slicing. We then capture and extract characteristic matrix corresponding to each gesture by using a synthetic aperture radar (SAR). Finally, we adopt dynamic time warping (DTW) techniques to recognize gestures by matching with the priori gesture fingerprint database. We implement our method using a COTS RFID device and evaluate it with 6 commercial tags. Experimental results demonstrate that this device free method is feasible and it can achieve a correct recognition rate of about 85%.
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