An Automatic and Robust Approach for Global Motion Estimation

In recent years, global motion estimation (GME) has become an important tool in the fields of video coding, video compression and computer vision. Estimating the correct global motion is often more difficult when the video scene contains large foreground objects. Previous approaches to addressing this problem have required the application of algorithm parameters that are sequence dependent or give inconsistent results for different video sequences. In this paper, we propose a fully automatic approach that can successfully estimate global motion in the presence of large foreground objects. The proposed algorithm determines an initial estimate of the foreground pixels and then reduces the effect of the remaining foreground by using a modified Lorentzian estimator. Experimental results show the proposed method produces superior and more consistent performance than some recent approaches for a wide range of sequences.