This paper introduces an accelerometer-based online gesture recognition system. Recognition of gestures can be utilised as a part of a human computer interaction for mobile devices, e.g. cell phones, PDAs and remote controllers. Gestures are captured with a small wireless sensor-box that produces three dimensional acceleration signal. Acceleration signal is preprocessed, vector quantised and finally classified using Hidden Markov Models. The design of online gesture recognition for mobile devices sets requirements for data processing. Thus, the system uses a small size codebook and simple preprocessing methods. The recognition accuracy of system is tested with gestures of four degrees of complexity. Experimental results show great potential for recognising simple and even more complex gestures with good accuracy.
['Sanna Kallio', 'Juha Kela', 'Jani Mäntyjärvi']
Online gesture recognition system for mobile interaction