Video stabilization motion filtering based on constraint unscented Kalman filter

A motion filtering method is proposed in this paper, which takes into consideration the existence of certain system constraints with respect to the amount of the corrective rotational and translational motions that can be applied on each video frame for stabilization. The interdependence between rotational and translational constraints is considered, and a constraint unscented Kalman filter （CUKF） algorithm is utilized to achieve a smoothly stabilized motion. The method is applied to stabilize each video frame, and the results reveal that the proposed approach improves the stabilization performance in comparison with the trivial approach.