Fast Multi-Frame Motion Estimation for Video Processing

Motion estimation is being utilized more and more in video post-production and display for a wide range of applications. These applications require accurate motion trajectories at low computational cost. This paper presents a novel motion estimation algorithm that combines the accuracy of MAP estimation with the speed of hierarchical block-matching algorithm (BMA). This MAP estimation uses three consecutive pictures, instead of the conventional two, and one previously estimated motion field to exploit the temporal correlation between motion fields and to determine motion in occluded areas. The optimization of the MAP estimation is performed using full search and implemented by means of look-up tables. The full search ensures that the optimization converges to the global minimum, while the look-up tables dramatically reduce the computational cost. Experiment results show that the proposed algorithm provides motion trajectories that are much more accurate than those obtained using the full-search BMA and hierarchical BMA. It is much faster than the full-search BMA, but slower than the hierarchical BMA.