The human visual system evolved in environments with statistical regularities. Binocular vision is adapted to these such that depth perception and eye movements are more precise, faster, and performed comfortably in environments consistent with the regularities. We measured the statistics of eye movements and binocular disparities in virtual-reality (VR) - gaming environments and found that they are quite different from those in the natural environment. Fixation distance and direction are more restricted in VR, and fixation distance is farther. The pattern of disparity across the visual field is less regular in VR and does not conform to a prominent property of naturally occurring disparities. From this we predict that double vision is more likely in VR than in the natural environment. We also determined the optimal screen distance to minimize discomfort due to the vergence-accommodation conflict, and the optimal nasal-temporal positioning of head-mounted display (HMD) screens to maximize binocular field of view. Finally, in a user study we investigated how VR content affects comfort and performance. Content that is more consistent with the statistics of the natural world yields less discomfort than content that is not. Furthermore, consistent content yields slightly better performance than inconsistent content.

Current eye-tracking techniques rely primarily on video-based tracking of components of the anterior surfaces of the eye. However, these trackers have several limitations. Their limited resolution precludes study of small fixational eye motion. Furthermore, many of these trackers rely on calibration procedures that do not offer a way to validate their eye motion traces. By comparison, retinal-image-based trackers can track the motion of the retinal image directly, at frequencies greater than 1kHz and with subarcminute accuracy. The retinal image provides a way to validate the eye position at any point in time, offering an unambiguous record of eye motion as a reference for the eye trace. The benefits of using scanning retinal imaging systems as eye trackers, however, comes at the price of different problems that are not present in video-based systems, and need to be solved to obtain robust eye traces. The current abstract provides an overview of retinal-image-based eye tracking methods, provides preliminary eye-tracking results from a tracking scanning-laser ophthalmoscope (TSLO), and proposes a new binocular line-scanning eye-tracking system.

In stereoscopic displays, such as those used in VR/AR headsets, our eyes are presented with two different views. The disparity between the views is typically used to convey depth cues, but it could be also used to enhance image appearance. We devise a novel technique that takes advantage of binocular fusion to boost perceived local contrast and visual quality of images. Since the technique is based on fixed tone curves, it has negligible computational cost and it is well suited for real-time applications, such as VR rendering. To control the trade-off between contrast gain and binocular rivalry, we conduct a series of experiments to explain the factors that dominate rivalry perception in a dichoptic presentation where two images of different contrasts are displayed. With this new finding, we can effectively enhance contrast and control rivalry in mono- and stereoscopic images, and in VR rendering, as confirmed in validation experiments.

Flat panels are by far the most common type of television screen. There are reasons, however, to believe that curved screens create a greater sense of immersion, reduce distracting reflections, and minimize some perceptual distortions that are commonplace with large televisions. To examine these possibilities, we calculated how curving the screen affects the field of view and the probability of seeing reflections of ambient lights. We find that screen curvature has a small beneficial effect on field of view and a large beneficial effect on the probability of seeing reflections. We also collected behavioral data to characterize perceptual distortions in various viewing configurations. We find that curved screens can in fact reduce problematic perceptual distortions on large screens, but that the benefit depends on the geometry of the projection on such screens.

Computer-graphics engineers and vision scientists want to generate images that reproduce realistic depth-dependent blur. Current rendering algorithms take into account scene geometry, aperture size, and focal distance, and they produce photorealistic imagery as with a high-quality camera. But to create immersive experiences, rendering algorithms should aim instead for perceptual realism. In so doing, they should take into account the significant optical aberrations of the human eye. We developed a method that, by incorporating some of those aberrations, yields displayed images that produce retinal images much closer to the ones that occur in natural viewing. In particular, we create displayed images taking the eye's chromatic aberration into account. This produces different chromatic effects in the retinal image for objects farther or nearer than current focus. We call the method ChromaBlur. We conducted two experiments that illustrate the benefits of ChromaBlur. One showed that accommodation (eye focusing) is driven quite effectively when ChromaBlur is used and that accommodation is not driven at all when conventional methods are used. The second showed that perceived depth and realism are greater with imagery created by ChromaBlur than in imagery created conventionally. ChromaBlur can be coupled with focus-adjustable lenses and gaze tracking to reproduce the natural relationship between accommodation and blur in HMDs and other immersive devices. It may thereby minimize the adverse effects of vergence-accommodation conflicts.

Head-mounted displays (HMDs) often cause discomfort and even nausea. Improving comfort is therefore one of the most significant challenges for the design of such systems. In this paper, we evaluate the effect of different HMD display configurations on discomfort. We do this by designing a device to measure human visual behavior and evaluate viewer comfort. In particular, we focus on one known source of discomfort: the vergence-accommodation (VA) conflict. The VA conflict is the difference between accommodative and vergence response. In HMDs the eyes accommodate to a fixed screen distance while they converge to the simulated distance of the object of interest, requiring the viewer to undo the neural coupling between the two responses. Several methods have been proposed to alleviate the VA conflict, including Depth-of-Field (DoF) rendering, focus-adjustable lenses, and monovision. However, no previous work has investigated whether these solutions actually drive accommodation to the distance of the simulated object. If they did, the VA conflict would disappear, and we expect comfort to improve. We design the first device that allows us to measure accommodation in HMDs, and we use it to obtain accommodation measurements and to conduct a discomfort study. The results of the first experiment demonstrate that only the focus-adjustable-lens design drives accommodation effectively, while other solutions do not drive accommodation to the simulated distance and thus do not resolve the VA conflict. The second experiment measures discomfort. The results validate that the focus-adjustable-lens design improves comfort significantly more than the other solutions.

Modern computer graphics are capable of generating highly photorealistic images. Although this can be considered a success for the computer graphics community, it has given rise to complex forensic and legal issues. A compelling example comes from the need to distinguish between computer-generated and photographic images as it pertains to the legality and prosecution of child pornography in the United States. We performed psychophysical experiments to determine the accuracy with which observers are capable of distinguishing computer-generated from photographic images. We find that observers have considerable difficulty performing this task—more difficulty than we observed 5 years ago when computer-generated imagery was not as photorealistic. We also find that observers are more likely to report that an image is photographic rather than computer generated, and that resolution has surprisingly little effect on performance. Finally, we find that a small amount of training greatly improves accuracy.

We present a technique for displaying three-dimensional imagery of general scenes with nearly correct focus cues on multi-plane displays. These displays present an additive combination of images at a discrete set of optical distances, allowing the viewer to focus at different distances in the simulated scene. Our proposed technique extends the capabilities of multi-plane displays to general scenes with occlusions and non-Lambertian effects by using a model of defocus in the eye of the viewer. Requiring no explicit knowledge of the scene geometry, our technique uses an optimization algorithm to compute the images to be displayed on the presentation planes so that the retinal images when accommodating to different distances match the corresponding retinal images of the input scene as closely as possible. We demonstrate the utility of the technique using imagery acquired from both synthetic and real-world scenes, and analyze the system's characteristics including bounds on achievable resolution.

Image-based rendering (IBR) creates realistic images by enriching simple geometries with photographs, e.g., mapping the photograph of a building façade onto a plane. However, as soon as the viewer moves away from the correct viewpoint, the image in the retina becomes distorted, sometimes leading to gross misperceptions of the original geometry. Two hypotheses from vision science state how viewers perceive such image distortions, one claiming that they can compensate for them (and therefore perceive scene geometry reasonably correctly), and one claiming that they cannot compensate (and therefore can perceive rather significant distortions). We modified the latter hypothesis so that it extends to street-level IBR. We then conducted a rigorous experiment that measured the magnitude of perceptual distortions that occur with IBR for façade viewing. We also conducted a rating experiment that assessed the acceptability of the distortions. The results of the two experiments were consistent with one another. They showed that viewers' percepts are indeed distorted, but not as severely as predicted by the modified vision science hypothesis. From our experimental results, we develop a predictive model of distortion for street-level IBR, which we use to provide guidelines for acceptability of virtual views and for capture camera density. We perform a confirmatory study to validate our predictions, and illustrate their use with an application that guides users in IBR navigation to stay in regions where virtual views yield acceptable perceptual distortions.

No abstract available.

We present a probabilistic model of how viewers may use defocus blur in conjunction with other pictorial cues to estimate the absolute distances to objects in a scene. Our model explains how the pattern of blur in an image together with relative depth cues indicates the apparent scale of the image's contents. From the model, we develop a semiautomated algorithm that applies blur to a sharply rendered image and thereby changes the apparent distance and scale of the scene's contents. To examine the correspondence between the model/algorithm and actual viewer experience, we conducted an experiment with human viewers and compared their estimates of absolute distance to the model's predictions. We did this for images with geometrically correct blur due to defocus and for images with commonly used approximations to the correct blur. The agreement between the experimental data and model predictions was excellent. The model predicts that some approximations should work well and that others should not. Human viewers responded to the various types of blur in much the way the model predicts. The model and algorithm allow one to manipulate blur precisely and to achieve the desired perceived scale efficiently.

Typical stereo displays provide incorrect focus cues because the light comes from a single surface. We describe a prototype stereo display comprising two independent fixed-viewpoint volumetric displays. Like autostereoscopic volumetric displays, fixed-viewpoint volumetric displays generate near-correct focus cues without tracking eye position, because light comes from sources at the correct focal distances. (In our prototype, from three image planes at different physical distances.) Unlike autostereoscopic volumetric displays, however, fixed-viewpoint volumetric displays retain the qualities of modern projective graphics: view-dependent lighting effects such as occlusion, specularity, and reflection are correctly depicted; modern graphics processor and 2-D display technology can be utilized; and realistic fields of view and depths of field can be implemented. While not a practical solution for general-purpose viewing, our prototype display is a proof of concept and a platform for ongoing vision research. The design, implementation, and verification of this stereo display are described, including a novel technique of filtering along visual lines using 1-D texture mapping.