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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...
This letter presents a region-based predictive decoding technique for end-to-end delay reduction in video communications. Video frames are predicted from past video data and displayed before they arrive at the decoder, thereby reducing the end-to-end delay. This problem is similar to whole-frame concealment, so we compare our method to a state-of-the-art whole-frame concealment algorithm. As demonstrated...
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...
In this paper, a frame-drop transcoding algorithm based on visual attention model is proposed for reducing the temporal resolution of a compressed video in order to fit the channel target bitrate. In the proposed method, the visual attention model is employed to measure frame complexity in order to determine whether frames should be skipped or not. Through the model analysis, we can preserve the significant...
In this paper, we consider aggregating multiple video streams and transmitting the merged stream over multiple error-prone paths. We propose a novel multi-stream error protection scheme based on packet division multiplexing access (PDMA) and cross-path forward error coding. Compared with the traditional time division multiplexing access (TDMA)-based error protection scheme, the proposed scheme outperforms...
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