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• W97059666 abstract "In this paper an improved, macroblock (MB) level, visual saliency algorithm, aimed at video compression, is presented. A Relevance Vector Machine (RVM) is trained over 3 dimensional feature vectors, pertaining to global, local and rarity measures of conspicuity, to yield probabalistic values which form the saliency map. These saliency values are used for non-uniform bit-allocation over video frames. A video compression architecture for propagation of saliency values, saving tremendous amount of computation, is also proposed." @default.
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• W97059666 date "2011-01-01" @default.
• W97059666 modified "2023-10-02" @default.
• W97059666 title "A Scheme for Attentional Video Compression" @default.
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• W97059666 doi "https://doi.org/10.1007/978-3-642-21786-9_74" @default.
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