a real-time 3D pointing gesture

recognition algorithm for natural human-robot interaction

(HRI). The recognition errors in previous pointing gesture

recognition algorithms are mainly caused by the low performance

of the hands tracking module and by the unreliability

of the direction estimate itself, therefore our proposed algorithm

uses 3D particle filter for achieving reliability in hand

tracking and cascade hidden Markov model (HMM) for a

robust estimate for the pointing direction. When someone

enters the field of view of the camera, his or her face and

two hands are located and tracked using the particle filters.

The first stage HMM takes the hand position estimate and

maps it to a more accurate position by modeling the kinematic

characteristics of finger pointing.