  Head gesture is a natural means of face-to-face communication between people
but the recognition of head gestures in the context of virtual reality and use
of head gesture as an interface for interacting with virtual avatars and
virtual environments have been rarely investigated. In the current study, we
present an approach for real-time head gesture recognition on head-mounted
displays using Cascaded Hidden Markov Models. We conducted two experiments to
evaluate our proposed approach. In experiment 1, we trained the Cascaded Hidden
Markov Models and assessed the offline classification performance using
collected head motion data. In experiment 2, we characterized the real-time
performance of the approach by estimating the latency to recognize a head
gesture with recorded real-time classification data. Our results show that the
proposed approach is effective in recognizing head gestures. The method can be
integrated into a virtual reality system as a head gesture interface for
interacting with virtual worlds.
