Fractional Fourier transform based cadence velocity diagram technique for human motion recognition

Human motion recognition (HMR) is playing an increasingly key role in many fields including public security, medical treatment and health care. In this paper, we propose a fractional Fourier transform (FrFT) based cadence-velocity diagram (CVD) based method, to improve the classification rate, which can effectively distinguish similar human motions in certain traditional feature domains such as the time-frequency (TF) domain. Besides, we also incorporate the feature in FrFT based CVD domain with the range feature, which can be regarded as the multi-domain feature. Then six human daily motions are then classified by the convolutional neural network (CNN) with the above multi-domain feature. Experimental results based on real data has demonstrated that the proposed method can achieve a high classification rate.