Abstract

In the paper, we addresses the problem of camera and object motion detection in compressed domain. The estimation of camera motion and the moving object segmentation have been widely stated in a variety of context for video analysis, because they are capable of providing essential clues for interpreting high-level semantic meanings of video sequences. A novel compressed domain motion estimation and segmentation scheme is presented and applied in this paper. The proposed algorithm uses MPEG-2 compressed motion vectors to undergo a spatial and temporal interpolation over several adjacent frames. An iterative rejection scheme based upon the affine model is exploited to effect global camera motion detection. The foreground spatiotemporal objects are separated from the background using the temporal consistency check to the output of the iterative segmentation. This consistency check process can help conglomerate the resulting foreground blocks and weed out unqualified blocks. Illustrative examples are provided to demonstrate the efficacy of the proposed approach.

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