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The computational modeling of the visual attention is receiving increasing attention from the computer vision community. Several bottom-up models have been proposed. In spite of their complexities, these models are still a basic description of our visual system. Review of resulting approaches of these efforts are presented in the first part of this paper. Limitations of these approaches are introduced and several research trends are given. Among them, the most important one might be the use of prior knowledge, conjointly with the low-level visual features. Concomitantly with visual attention (VA) modeling progress, the image and video processing community is increasingly considering VA models in different fields or services. Current and future applications of VA models are discussed in the second part.