Recently, there has been great interest among vision researchers in developing computational models that predict the distribution of saccadic endpoints in naturalistic scenes. In many of these studies, subjects are instructed to view scenes without any particular task in mind so that stimulus-driven (bottom-up) processes guide visual attention. However, whenever there is a search task, goal-driven (top-down) processes tend to dominate guidance, as indicated by attention being systematically biased toward image features that resemble those of the search target. In the present study, we devise a top-down model of visual attention during search in complex scenes based on similarity between the target and regions of the search scene. Similarity is defined for several feature dimensions such as orientation or spatial frequency using a histogram-matching technique. The amount of attentional guidance across visual feature dimensions is predicted by a previously introduced informativeness measure. We use eye-movement data gathered from participants’ search of a set of naturalistic scenes to evaluate the model. The model is found to predict the distribution of saccadic endpoints in search displays nearly as accurately as do other observers’ eye-movement data in the same displays.

In this selective review, we examine key findings on eye movements when viewing advertisements. We begin with a brief, general introduction to the properties and neural underpinnings of saccadic eye movements. Next, we provide an overview of eye movement behavior during reading, scene perception, and visual search, since each of these activities is, at various times, involved in viewing ads. We then review the literature on eye movements when viewing print ads and warning labels (of the kind that appear on alcohol and tobacco ads), before turning to a consideration of advertisements in dynamic media (television and the Internet). Finally, we propose topics and methodological approaches that may prove to be useful in future research.

While our frequent saccades allow us to sample the complex visual environment in a highly efficient manner, they also raise certain challenges for interpreting and acting upon visual input. In the present, selective review, we discuss key findings from the domains of cognitive psychology, visual perception, and neuroscience concerning two such challenges: (1) maintaining the phenomenal experience of visual stability despite our rapidly shifting gaze, and (2) integrating visual information across discrete fixations. In the first two sections of the article, we focus primarily on behavioral findings. Next, we examine the possibility that a neural phenomenon known as predictive remapping may provide an explanation for aspects of transsaccadic processing. In this section of the article, we delineate and critically evaluate multiple proposals about the potential role of predictive remapping in light of both theoretical principles and empirical findings.Keywords Eye movements . Predictive remapping . Saccades . Transsaccadic integration . Transsaccadic perception . Transsaccadic processing . Visual stability During waking hours, our eyes dart from one location to the next about three times every second (Schiller, 1998). These fast, darting movements called saccades take place in alternating sequence with short periods known as fixations when the eyes remain relatively still. It is during fixations that we obtain useful information from the visual world, viewing a sort of 'snapshot' of the scene from the current vantage point (Neisser, 1967). Because only the fovea, a central region of the retina spanning about 2°of visual angle, is specialized for high acuity processing, we acquire detailed visual information from only a small part of the world during any given fixation (Jones & Higgins, 1947).Saccades allow the proximal stimulus of vision, the retinal image, to be selected quickly and efficiently based on processing requirements. Both the locations we fixate and the durations of our fixations reflect online selection of critical information from the visual environment (for reviews, see Rayner, 1998Rayner, , 2009). This seems an enormously beneficial attribute of the system. Our continually shifting gaze, however, also raises potential challenges for interpreting and acting upon the information acquired.First, the mobility of the eye raises the question of how we plan actions based on visual position information. Because our eyes move frequently about, a given retinal location does not map onto a unique location in space relative to the arms, legs, or other motor effectors. Therefore, some means of tracking the eye's current position relative to the effectors seems important for calculating the appropriate movement vector at any given moment. While this is a critical issue, it lies somewhat beyond the scope of the present article, which focuses more narrowly on how we perceive and represent the visual world across saccades (for reviews focusing on transsaccadic updating for motor control, see Klier & Angelaki...

Color coding is used to guide attention in computer displays for such critical tasks as baggage screening or air traffic control. It has been shown that a display object attracts more attention if its color is more similar to the color for which one is searching. However, what does similar precisely mean? Can we predict the amount of attention that a display color will receive during a search for a given target color? To tackle this question, two color-search experiments measuring the selectivity of saccadic eye movements and mapping out its underlying color space were conducted. A variety of mathematical models, predicting saccadic selectivity for given target and display colors, were devised and evaluated. The results suggest that applying a Gaussian function to a weighted Euclidean distance in a slightly modified HSI color space is the best predictor of saccadic selectivity in the chosen paradigm. Hue and intensity information by itself provides a basis for useful predictors, spanning a possibly spherical color space of saccadic selectivity. Although the current models cannot predict saccadic selectivity values for a wide variety of visual search tasks, they reveal some characteristics of color search that are of both theoretical and applied interest, such as for the design of human-computer interfaces.