A fast predictive block matching motion estimation algorithm based on spatio temporal correlation information

Abstract

Motion estimation is an important and computationally intensive task in video coding applications. Fast block matching algorithms reduce the computational complexity of motion estimation at the expense of accuracy. Fast motion estimation algorithms often assume monotonic error surface in order to speed up the computations. The argument against this assumption is that the search might be trapped in local minimum resulting in inaccurate motion estimates. This paper investigates the state-of-the-art techniques for block based motion estimation and presents an approach to improve the performance of block-based motion estimation algorithms. Specifically, this paper suggests a simple scheme that includes spatiotemporal neighborhood information for obtaining better estimates of the motion vectors. The predictive motion vector is then chosen as the initial search center. This predictive search center is found to be closer to the global minimum and thus decreases the effects of the monotonic error surface assumption and its impact on the motion field estimates. Based on the prediction, the algorithm also chooses between center biased or uniform approach for slow or fast moving sequences. The experiments presented in this paper demonstrate the efficiency of the proposed approach.