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Surveillance video privacy protection has drawn significant attention recently. In this paper, we describe a privacy protected video surveillance system which utilizes the emerging compressive sensing (CS) theory. Privacy regions are scrambled through block based CS sampling on quantized coefficients during compression. Security is ensured by key controlled chaotic sequence which is used to construct...
We propose a compressive video sensing scheme based on user attention model (UAM) for real video sequences acquisition. In this work, for every group of consecutive video frames, we set the first frame as reference frame and build a UAM with visual rhythm analysis (VRA) to automatically determine region-of-interest (ROI) for non-reference frames. The determined ROI usually has significant movement...
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