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This paper presents a new algorithm for moving object detection in the H.264/AVC compressed domain which relies on motion vector information. In contrast to other motion vector-based algorithms, special attention is paid to noisy motion vectors as they highly decrease the performance of these algorithms. We propose to estimate the reliability of motion vectors by comparing them with projected motion vectors from surrounding frames. As such, noisy motion vectors are localized. By combining this information with the magnitude of motion vectors, foreground objects are distinguished. Experimental results demonstrate that our algorithm achieves significantly better segmentation quality compared to other motion vector-based approaches

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