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In this paper, we proposed a robust moving video object segmentation algorithm using features in the MPEG compressed domain. We first cluster the motion vectors and produce a motion mask. Then, a difference mask at 8 x 8 block size is extracted from the DC image by background subtraction method. Finally, the motion mask and the difference mask are combined conditionally to generate the final object mask based on a set of rules that are application specified and is obtained with learning or heuristic based methods. The experimental results show that this object segmentation scheme is more robust than those using DC image or motion vectors only.