ROBUST GLOBAL MOTION ESTIMATION USING MOTION VECTORS OF VARIABLE SIZE BLOCKS AND AUTOMATIC MOTION MODEL SELECTION

A new approach for highly robust and precise global motion estimation (GME) using motion vectors (MVs) is presented. We show that this approach obtains precise higher-order short-term motion parameters for global motion using motion vectors solely. The approach is general and works for different mathematical methods including least-squares and Newton-Raphson method. We show that the approach is suitable for fixed block sizes from plain full-search block-matching as well as for arbitrary block sizes from video streams compressed with H.264/AVC reference encoder. The proposed approach is compared against four other known MV-based GME (MV-GME) methods. Our results show that the approach is significantly more robust and obtains higher precision for global motion parameters in terms of background motion compensation, especially if moving objects occur. In addition, the results are as good as results from precise pixel-based GME methods or even better while the presented MV-GME methods have very low computational costs.