Real-time head and hand tracking based on 2.5D data

A novel real-time algorithm for head and hand tracking is proposed in this paper. This approach is based on 2.5D data from a range camera, which is exploited to resolve ambiguities and overlaps. Experimental results show high robustness against partial occlusions and fast movements. The estimated positions are fairly stable, allowing the extraction of accurate trajectories which may be used for gesture classification purposes.