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A new computational scheme for visual attention modeling is proposed. It adopts both low-level and high-level features to predict visual attention from a video signal and fuses the features by using machine learning. We show that such a scheme is more robust than those using purely single level features. Unlike conventional techniques, our scheme is able to avoid perceptual mismatch between the estimated...
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