Accelerometer Based Gesture Recognition Using Fusion Features and SVM

In this paper, a gesture recognition system based on single tri-axis accelerometer mounted on a cell phone is proposed. The authors present a novel human computer interaction for cell phone through recognizing seventeen complex gestures. A new feature fusion method for gesture recognition based on time-domain and frequency-domain is proposed. First of all, they extract the time-domain features from acceleration data, that is short-time energy. Secondly, they extract the hybrid features which combine Wavelet Packet Decomposition with Fast Fourier Transform. Finally, they fuse these two categories features together and employ the principal component analysis to reduce dimension of fusion features.