Most Global Motion Estimation (GME) Methods Are Oriented To Video Coding While Video Object Segmentation Methods Either Assume No Global Motion (GM) Or Directly Adopt A Coding Oriented Method To Compensate For GM. This Paper Proposes A Hierarchical Differential GME Method Oriented To Video Object Segmentation. A Scheme Which Combines Three-step Search And Motion Parameters Prediction Is Proposed For Initial Estimation To Increase Efficiency. A Robust Estimator That Uses Object Information To Reject Outliers Introduced By Local Motion Is Also Proposed. For The First Frame, When The Object Information Is Unavailable, A Robust Estimator Is Proposed Which Rejects Outliers By Examining Their Distribution In Local Neighborhoods Of The Error Between The Current And The Motion-compensated Previous Frame. Subjective And Objective Results Show That The Proposed Method Is More Robust, More Oriented To Video Object Segmentation, And Faster Than The Referenced Methods.
