The inspection of very large images by eye-gaze control

The increasing availability and accuracy of eye gaze detection equipment has encouraged its use for both investigation and control. In this paper we present novel methods for navigating and inspecting extremely large images solely or primarily using eye gaze control. We investigate the relative advantages and comparative properties of four related methods: Stare-to-Zoom (STZ), in which control of the image position and resolution level is determined solely by the user’s gaze position on the screen; Head-to-Zoom (HTZ) and Dual-to-Zoom (DTZ), in which gaze control is augmented by head or mouse actions; and Mouse-to-Zoom (MTZ), using conventional mouse input as an experimental control. # The need to inspect large images occurs in many disciplines, such as mapping, medicine, astronomy and surveillance. Here we consider the inspection of very large aerial images, of which Google Earth is both an example and the one employed in our study. We perform comparative search and navigation tasks with each of the methods described, and record user opinions using the Swedish User-Viewer Presence Questionnaire. We conclude that, while gaze methods are effective for image navigation, they, as yet, lag behind more conventional methods and interaction designers may well consider combining these techniques for greatest effect

A system for gaze-contingent image analysis and multi-sensorial image display

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WAYLA - Generating Images from Eye Movements

We present a method for reconstructing images viewed by observers based only on their eye movements. By exploring the relationships between gaze patterns and image stimuli, the "What Are You Looking At?" (WAYLA) system learns to synthesize photo-realistic images that are similar to the original pictures being viewed. The WAYLA approach is based on the Conditional Generative Adversarial Network (Conditional GAN) image-to-image translation technique of Isola et al. We consider two specific applications - the first, of reconstructing newspaper images from gaze heat maps, and the second, of detailed reconstruction of images containing only text. The newspaper image reconstruction process is divided into two image-to-image translation operations, the first mapping gaze heat maps into image segmentations, and the second mapping the generated segmentation into a newspaper image. We validate the performance of our approach using various evaluation metrics, along with human visual inspection. All results confirm the ability of our network to perform image generation tasks using eye tracking data

Behavioral biases when viewing multiplexed scenes:scene structure and frames of reference for inspection

Where people look when viewing a scene has been a much explored avenue of vision research (e.g., see Tatler, 2009). Current understanding of eye guidance suggests that a combination of high and low-level factors influence fixation selection (e.g., Torralba et al., 2006), but that there are also strong biases toward the center of an image (Tatler, 2007). However, situations where we view multiplexed scenes are becoming increasingly common, and it is unclear how visual inspection might be arranged when content lacks normal semantic or spatial structure. Here we use the central bias to examine how gaze behavior is organized in scenes that are presented in their normal format, or disrupted by scrambling the quadrants and separating them by space. In Experiment 1, scrambling scenes had the strongest influence on gaze allocation. Observers were highly biased by the quadrant center, although physical space did not enhance this bias. However, the center of the display still contributed to fixation selection above chance, and was most influential early in scene viewing. When the top left quadrant was held constant across all conditions in Experiment 2, fixation behavior was significantly influenced by the overall arrangement of the display, with fixations being biased toward the quadrant center when the other three quadrants were scrambled (despite the visual information in this quadrant being identical in all conditions). When scenes are scrambled into four quadrants and semantic contiguity is disrupted, observers no longer appear to view the content as a single scene (despite it consisting of the same visual information overall), but rather anchor visual inspection around the four separate “sub-scenes.” Moreover, the frame of reference that observers use when viewing the multiplex seems to change across viewing time: from an early bias toward the display center to a later bias toward quadrant centers

Training methods for facial image comparison: a literature review

This literature review was commissioned to explore the psychological literature relating to facial image comparison with a particular emphasis on whether individuals can be trained to improve performance on this task. Surprisingly few studies have addressed this question directly. As a consequence, this review has been extended to cover training of face recognition and training of different kinds of perceptual comparisons where we are of the opinion that the methodologies or findings of such studies are informative. The majority of studies of face processing have examined face recognition, which relies heavily on memory. This may be memory for a face that was learned recently (e.g. minutes or hours previously) or for a face learned longer ago, perhaps after many exposures (e.g. friends, family members, celebrities). Successful face recognition, irrespective of the type of face, relies on the ability to retrieve the to-berecognised face from long-term memory. This memory is then compared to the physically present image to reach a recognition decision. In contrast, in face matching task two physical representations of a face (live, photographs, movies) are compared and so long-term memory is not involved. Because the comparison is between two present stimuli rather than between a present stimulus and a memory, one might expect that face matching, even if not an easy task, would be easier to do and easier to learn than face recognition. In support of this, there is evidence that judgment tasks where a presented stimulus must be judged by a remembered standard are generally more cognitively demanding than judgments that require comparing two presented stimuli Davies & Parasuraman, 1982; Parasuraman & Davies, 1977; Warm and Dember, 1998). Is there enough overlap between face recognition and matching that it is useful to look at the literature recognition? No study has directly compared face recognition and face matching, so we turn to research in which people decided whether two non-face stimuli were the same or different. In these studies, accuracy of comparison is not always better when the comparator is present than when it is remembered. Further, all perceptual factors that were found to affect comparisons of simultaneously presented objects also affected comparisons of successively presented objects in qualitatively the same way. Those studies involved judgments about colour (Newhall, Burnham & Clark, 1957; Romero, Hita & Del Barco, 1986), and shape (Larsen, McIlhagga & Bundesen, 1999; Lawson, Bülthoff & Dumbell, 2003; Quinlan, 1995). Although one must be cautious in generalising from studies of object processing to studies of face processing (see, e.g., section comparing face processing to object processing), from these kinds of studies there is no evidence to suggest that there are qualitative differences in the perceptual aspects of how recognition and matching are done. As a result, this review will include studies of face recognition skill as well as face matching skill. The distinction between face recognition involving memory and face matching not involving memory is clouded in many recognition studies which require observers to decide which of many presented faces matches a remembered face (e.g., eyewitness studies). And of course there are other forensic face-matching tasks that will require comparison to both presented and remembered comparators (e.g., deciding whether any person in a video showing a crowd is the target person). For this reason, too, we choose to include studies of face recognition as well as face matching in our revie