Abstract
Wearable devices with accelerometer, gyroscope and so on are available wherever and whenever users need them. In this study, we construct the head gesture recognition system using wearable sensor with accelerometer. We use a glasses-like wearable sensor to provide easy-to-use system. In order to recognize users head gestures such as "nodding", "shaking" and so on, we extract feature vectors using principal component analysis (PCA) for the acceleration timeseries data and then classify the data by k-nearest neighbor (k-NN) or multi-layer perceptron (MLP) classification method. Moreover, we realize the real-time head gesture recognition system. Through the experiments of the head gesture recognition for the multiple users, we confirm the effectiveness of our system.
