一种基于连续波雷达的手势识别方法

A Hand Gesture Recognition Method Based on Continuous Wave Radar

为了解决依靠光学传感器进行手势识别对外部环境依赖较大的问题,提出了一种基于连续波(Continuous Wave,CW)雷达的手势识别方法,并建立了4种手势动作的回波数据库。首先,对CW雷达回波进行短时傅里叶变换(Short-Time Fourier Transform,STFT)获取手势动作的时频谱;然后,通过设立阈值将时频谱中的背景杂波去除;接下来,对处理后的时频谱提取方向梯度直方图(Histogram of Oriented Gradient,HOG)特征;最后,采用支持向量机(Support Vector Machine,SVM)作为分类器,以HOG特征作为输入进行手势识别。实验结果表明,所提方法在普通室内环境下的识别精度超过95%,能够对典型的手势动作进行有效识别。

To solve the problem that external environment affects recognition accurary,a new hand gesture recognition method based on continuous wave(CW)radar is investigated,and a dataset of four typical hand gestures echo wave is generated.Firstly,the short-time Fourier transform(STFT)of CW radar echoes from hand gestures is applied to produce the time-frequency spectrograms of hand gestures.Next,the background clutter in the time-frequency spectrograms is removed by setting up thresholds.Then,the histogram of oriented gradient(HOG)feature is extracted from the processed time-frequency spectrograms.Finally,the support vector machine(SVM)is used as a classifier and the HOG features are used as input for gesture recognition.The experimental results show that the recognition accuracy of the proposed method reaches more than 95%in a normal indoor environment,and it can effectively recognize typical hand gestures.