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In this paper, we propose an unsupervised segmentation algorithm for extracting moving objects/regions from compressed video using Markov Random Field (MRF) classification. First, motion vectors (MVs) are quantized into several representative classes, from which MRF priors are estimated. Then, a coarse segmentation map of the MV field is obtained using a maximum a posteriori estimate of the MRF label...
In this paper, we propose a coarse-to-fine segmentation method for extracting moving regions from compressed video. First, motion vectors are clustered to provide a coarse segmentation of moving regions at block level. Second, boundaries between moving regions are identified, and finally, a fine segmentation is performed within boundary regions using edge and color information. Experimental results...
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