Recent studies of eye movements in reading and other information processing tasks, such as music reading, typing, visual search, and scene perception, are reviewed. The major emphasis of the review is on reading as a specific example of cognitive processing. Basic topics discussed with respect to reading are (a) the characteristics of eye movements, (b) the perceptual span, (c) integration of information across saccades, (d) eye movement control, and (e) individual differences (including dyslexia). Similar topics are discussed with respect to the other tasks examined. The basic theme of the review is that eye movement data reflect moment-to-moment cognitive processes in the various tasks examined. Theoretical and practical considerations concerning the use of eye movement data are also discussed. Many studies using eye movements to investigate cognitive processes have appeared over the past 20 years. In an earlier review, I (Rayner, 1978b) argued that since the mid-1970s we have been in a third era of eye movement research and that the success of research in the current era would depend on the ingenuity of researchers in designing interesting and informative

Recent computational models of cognition have made good progress in accounting for the visual processes needed to encode external stimuli. However, these models typically incorporate simplified models of visual processing that assume a constant encoding time for all visual objects and do not distinguish between eye movements and shifts of attention. This paper presents a domain-independent computational model, EMMA, that provides a more rigorous account of eye movements and visual encoding and their interaction with a cognitive processor. The visual-encoding component of the model describes the effects of frequency and foveal eccentricity when encoding visual objects as internal representations. The eye-movement component describes the temporal and spatial characteristics of eye movements as they arise from shifts of visual attention. When integrated with a cognitive model, EMMA generates quantitative predictions concerning when and where the eyes move, thus serving to relate higher-level cognitive processes and attention shifts with lower-level eye-movement behavior. The paper evaluates EMMA in three illustrative domains — equation solving, reading, and visual search — and demonstrates how the model accounts for aspects of behavior that simpler models of cognitive and visual processing fail to explain.

This article describes and evaluates a class of methods for performing automated analysis of eye-movement protocols. Although eye movements have become increasingly popular as a tool for investigating user behavior, they can be extremely difficult and tedious to analyze. In this article we propose an approach to automating eye-movement protocol analysis by means of tracing—relating observed eye movements to the sequential predictions of a process model. We present three tracing methods that provide fast and robust analysis and alleviate the equipment noise and individual variability prevalent in typical eye-movement protocols. We also describe three applications of the tracing methods that demonstrate how the methods facilitate the use of eye movements in the study of user behavior and the inference of user intentions. 1.

Visual cognition depends critically on the ability to make rapid eye movements known as saccades that orient the fovea over targets of interest in a visual scene. Saccades are known to be ballistic: the pattern of muscle activation for foveating a prespecified target location is computed prior to the movement and visual feedback is precluded. Despite these distinctive properties, there has been no general model of the saccadic targeting strategy employed by the human visual system during visual search in natural scenes. This paper proposes a model for saccadic targeting that uses iconic scene representations derived from oriented spatial filters at multiple scales. Visual search proceeds in a coarse-to-fine fashion with the largest scale filter responses being compared first. The model was empirically tested by comparing its performance with actual eye movement data from human subjects in a natural visual search task; preliminary results indicate substantial agreement between eye movements predicted by the model and those recorded from human subjects.

Scanpath Theory on Web 2 The somewhat controversial and often-discussed scanpath theory of visual perception was tested using Web pages as visual stimuli. In 1971, Noton and Stark defined "scanpaths " as repetitive sequences of fixations and saccades that occur upon re-exposure to a visual stimulus, facilitating recognition of that stimulus. Since Internet users are repeatedly exposed to certain visual displays of information, the Web is an ideal stimulus to test this theory. Eye-movement data were recorded for subjects ' repeated viewings of three kinds of Internet pages-- a portal page, an advertising page and a news story page-- over the course of a week. Scanpaths were compared using a string-edit method to measure resemblance between sequences.

We view scenes in the real world by moving our eyes three to four times each second, and integrating information across subsequent fixations (foveation points). By taking advantage of this fact, in this paper we propose an original approach to partitioning of a video into shots based on a foveated representation of the video. More precisely, the shotchange detection method is related to the computation, at each time instant, of a consistency measure of the fixation sequences generated by an ideal observer looking at the video. The proposed scheme aims at detecting both abrupt and gradual transitions between shots using a single technique, rather than a set of dedicated methods. Results on videos of various content types are reported and validate the proposed approach Index Terms--- Attentive Vision, Video Segmentation, Shot Detection, Hard Cuts, Dissolves.

This paper contains extensive tabular summaries of the capabilities of these devices. Although these tables are often necessarily incomplete they often contain useful pointers to workers in the field. Table 2 contains summarized information on the force feedback devices reviewed in [33]

The intention here is to focus on some motor-oriented approaches to the spatial functions of the brain and to see how far they contribute to our understanding of the way in which the internal metric of spatial information is neurally encoded. A motor-oriented approach assumes that the principal metric for coding

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Abstract. Active vision may be useful to perform landmark-based navigation where landmark relationship requires active scanning of the environment. In this article we explore this hypothesis by evolving the neural system controlling vision and behavior of a mobile robot equipped with a pan/tilt camera so that it can discriminate visual patterns and arrive at the goal zone. The experimental setup employed in this article requires the robot to actively move its gaze direction and integrate information over time in order to accomplish the task. We show that the evolved robot can detect separate features in a sequential manner and discriminate the spatial relationships. An intriguing hypothesis on landmark-based navigation in insects derives from the present results. 1