Global motion estimation (GME) from motion vector (MV) field in compressed domain greatly reduces the complexity of conventional pixel-based GME. However, outlier MVs, caused by noise or foreground objects, may reduce the accuracy of MV-based GME. In this paper, we propose a cascade-of-rejectors approach for removing MV outliers to achieve efficient and accurate GME. Experimental results show that the proposed MV outlier rejection cascade significantly lowers the complexity MV-based GME, with an accuracy close to or better than state-of-the-art methods.
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