安卓平台下基于传感器的手势识别研究

In this paper, we designed and implemented an accelerometer-based gesture recognition system using dynamic time warping (DTW) on intelligent terminal with Android. In this system, the start and end of the data collection process is automatically determined by acceleration waveform. In pretreatment phase, we propose a waveform compensation algorithm to solve the problems caused by the amplitude range of the accelerometer and use the coordinate transformation theory to alleviate the angle offset. In training phase, we use dynamic time warping and affinity propagation (AP) to extract clusters and exemplars. To test the system's performance, a dictionary of 10 gestures is defined and a database consists of 3800 samples is created from 14 participants. Test results have shown that the proposed system achieves a good performance in gesture recognition.