Models of bottom-up and top-down visual attention

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Task and context determine where you look. (2016, methodology): “The gaze allocation was modeled (1) with a random gaze distribution in which a location weighted by the subject’s distribution of gaze relative to the field of view and (2) according to the saliency model Itti (2000). Given that the standard saliency model contains approximately 40 free parameters, ”
State-of-the-Art in Visual Attention Modeling (2013, background): “A rich stream of visual data (10 8 -10 9 bits) enters our eyes every second [1], [2].”
A Novel Multiresolution Spatiotemporal Saliency Detection Model and Its Applications in Image and Video Compression (2010, neutral): “15 [11] and [21].”
Learning to Detect A Salient Object (2007, background): “There are many applications for visual attention, for example, automatic image cropping [23], adaptive image display on small devices [4], image/video compression, advertising design [7], and image collection browsing.”
Modeling attention to salient proto-objects (2006, neutral): “(2) deviate from the model by Itti et al. (1998) in the definition of yellow and in normalizing by max(r, g, b) rather than the average (r + b+ g)/3.”