Efficient global motion estimation algorithm using recursive least squares

Global motion estimation plays an important role in video compensation and video analysis. We present an efficient method to estimate global motion parameters. First, a feature point selection scheme that exploits the symmetry properties of camera motion is developed. Then, we use parametric motion models to characterize global motion and a recursive least-squares scheme to accelerate the computation of parameter estimation. In the proposed method, the motion vectors in the background area are selected to estimate the parameters of motion models, which improves estimate reliability. Simulation results show that the proposed method gives better performance than the previous methods in terms of the computational efficiency and the estimate accuracy.