Improved initial value prediction for global motion estimation

Global motion estimation (GME) algorithms have an imperative role in object-based applications. Gradient-based GME is a well known method among these algorithms. Such algorithms require an initial value for their initialization step. Well estimation of this value plays a significant role in the accuracy of GME. This work introduces a simple but efficient technique for initial value prediction of GME. This technique employs a long-term predictor as well as global motions of previous frames. Simulations results demonstrate faster convergence and less computational complexity of the proposed method versus common presented techniques in the literature with almost same efficiency.