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PurposeTo examine perceptual adaptation when people wear spectacles that produce unequal retinal image magnification.MethodsTwo groups of 15 participants (10 male; mean age 25.6 ± 4.9 years) wore spectacles with a 3.8% horizontal magnifier over one eye. The continuous-wear group wore the spectacles for 5 hours straight. The intermittent-wear group wore them for five 1-hour intervals. To measure slant and shape distortions produced by the spectacles, participants adjusted visual stimuli until they appeared frontoparallel or equiangular, respectively. Adaptation was quantified as the difference in responses at the beginning and end of wearing the spectacles. Aftereffects were quantified as the difference before and after removing the spectacles. We hypothesized that intermittent wear may lead to visual cue reweighting, so we fit a cue combination model to the data and examined changes in weights given to perspective and binocular disparity slant cues.ResultsBoth groups experienced significant shape adaptation and aftereffects. The continuous-wear group underwent significant slant adaptation and the intermittent group did not, but there was no significant difference between groups, suggesting that the difference in adaptation was negligible. There was no evidence for cue reweighting in the intermittent wear group, but unexpectedly, the weight given to binocular disparity cues for slant increased significantly in the continuous-wear group.ConclusionsWe did not find strong evidence that adaptation to spatial distortions differed between the two groups. However, there may be differences in the cue weighting strategies employed when spectacles are worn intermittently or continuously.

In near-eye display systems that support three-dimensional (3D) augmented and virtual reality, a central factor in determining the user experience is the size of the eyebox. The eyebox refers to a volume where the eye receives an acceptable view of the image with respect to a set of criteria and thresholds. The size and location of this volume are primarily driven by optical architecture choices in which designers trade-off a number of constraints, such as field of view, image quality, and product design. It is thus important to clearly quantify how design decisions affect the properties of the eyebox. Recent work has started evaluating the eyebox in 3D based purely on optical criteria. However, such analyses do not incorporate perceptual criteria that determine visual quality, which are particularly important for binocular 3D systems. To address this limitation, we introduce the framework of a perceptual eyebox. The perceptual eyebox is the volume where the eye(s) must be located for the user to experience a visual percept falling within a perceptually-defined criterion. We combine optical and perceptual data to characterize an example perceptual eyebox for display visibility in augmented reality. The key contributions in this paper include: comparing the perceptual eyebox for monocular and binocular display designs, modeling the effects of user eye separation, and examining the effects of eye rotation on the eyebox volume.

Binocular fusion relies on matching points in the two eyes that correspond to the same physical feature in the world; however, not all world features are binocularly visible. Near depth edges, some regions of a scene are often visible to only one eye (so-called half occlusions). Accurate detection of these monocularly visible regions is likely to be important for stable visual perception. If monocular regions are not detected as such, the visual system may attempt to binocularly fuse non-corresponding points, which can result in unstable percepts. We investigated the hypothesis that the visual system capitalizes on statistical regularities associated with depth edges in natural scenes to aid binocular fusion and facilitate perceptual stability. By sampling from a large set of stereoscopic natural images with co-registered distance information, we found evidence that monocularly visible regions near depth edges primarily result from background occlusions. Accordingly, monocular regions tended to be more visually similar to the adjacent binocularly visible background region than to the adjacent binocularly visible foreground. Consistent with our hypothesis, perceptual experiments showed that perception tended to be more stable when the image properties of the depth edge were statistically more likely given the probability of occurrence in natural scenes (i.e., when monocular regions were more visually similar to the binocular background). The generality of these results was supported by a parametric study with simulated environments. Exploiting regularities in natural environments may allow the visual system to facilitate fusion and perceptual stability when both binocular and monocular regions are visible.

People typically rely heavily on visual information when finding their way to unfamiliar locations. For individuals with reduced vision, there are a variety of navigational tools available to assist with this task if needed. However, for wayfinding in unfamiliar indoor environments the applicability of existing tools is limited. One potential approach to assist with this task is to enhance visual information about the location and content of existing signage in the environment. With this aim, we developed a prototype software application, which runs on a consumer head-mounted augmented reality (AR) device, to assist visually impaired users with sign-reading. The sign-reading assistant identifies real-world text (e.g., signs and room numbers) on command, highlights the text location, converts it to high contrast AR lettering, and optionally reads the content aloud via text-to-speech. We assessed the usability of this application in a behavioral experiment. Participants with simulated visual impairment were asked to locate a particular office within a hallway, either with or without AR assistance (referred to as the AR group and control group, respectively). Subjective assessments indicated that participants in the AR group found the application helpful for this task, and an analysis of walking paths indicated that these participants took more direct routes compared to the control group. However, participants in the AR group also walked more slowly and took more time to complete the task than the control group. The results point to several specific future goals for usability and system performance in AR-based assistive tools.

People typically rely heavily on visual information when finding their way to unfamiliar locations. For individuals with reduced vision, there are a variety of navigational tools available to assist with this task if needed. However, for wayfinding in unfamiliar indoor environments the applicability of existing tools is limited. One potential approach to assist with this task is to enhance visual information about the location and content of existing signage in the environment. With this aim, we developed a prototype software application, which runs on a consumer head-mounted augmented reality (AR) device, to assist visually impaired users with sign-reading. The sign-reading assistant identifies real-world text (e.g., signs and room numbers) on command, highlights the text location, converts it to high contrast AR lettering, and optionally reads the content aloud via text-to-speech. We assessed the usability of this application in a behavioral experiment. Participants with simulated visual impairment were asked to locate a particular office within a hallway, either with or without AR assistance (referred to as the AR group and control group, respectively). Subjective assessments indicated that participants in the AR group found the application helpful for this task, and an analysis of walking paths indicated that these participants took more direct routes compared to the control group. However, participants in the AR group also walked more slowly and took more time to complete the task than the control group. The results point to several specific future goals for usability and system performance in AR-based assistive tools.

SignificanceFor people with limited vision, wearable displays hold the potential to digitally enhance visual function. As these display technologies advance, it is important to understand their promise and limitations as vision aids.PurposeThe aim of this study was to test the potential of a consumer augmented reality (AR) device for improving the functional vision of people with near-complete vision loss.MethodsAn AR application that translates spatial information into high-contrast visual patterns was developed. Two experiments assessed the efficacy of the application to improve vision: an exploratory study with four visually impaired participants and a main controlled study with participants with simulated vision loss (n = 48). In both studies, performance was tested on a range of visual tasks (identifying the location, pose and gesture of a person, identifying objects, and moving around in an unfamiliar space). Participants' accuracy and confidence were compared on these tasks with and without augmented vision, as well as their subjective responses about ease of mobility.ResultsIn the main study, the AR application was associated with substantially improved accuracy and confidence in object recognition (all P < .001) and to a lesser degree in gesture recognition (P < .05). There was no significant change in performance on identifying body poses or in subjective assessments of mobility, as compared with a control group.ConclusionsConsumer AR devices may soon be able to support applications that improve the functional vision of users for some tasks. In our study, both artificially impaired participants and participants with near-complete vision loss performed tasks that they could not do without the AR system. Current limitations in system performance and form factor, as well as the risk of overconfidence, will need to be overcome.

SignificanceFor people with limited vision, wearable displays hold the potential to digitally enhance visual function. As these display technologies advance, it is important to understand their promise and limitations as vision aids.PurposeThe aim of this study was to test the potential of a consumer augmented reality (AR) device for improving the functional vision of people with near-complete vision loss.MethodsAn AR application that translates spatial information into high-contrast visual patterns was developed. Two experiments assessed the efficacy of the application to improve vision: an exploratory study with four visually impaired participants and a main controlled study with participants with simulated vision loss (n = 48). In both studies, performance was tested on a range of visual tasks (identifying the location, pose and gesture of a person, identifying objects, and moving around in an unfamiliar space). Participants' accuracy and confidence were compared on these tasks with and without augmented vision, as well as their subjective responses about ease of mobility.ResultsIn the main study, the AR application was associated with substantially improved accuracy and confidence in object recognition (all P < .001) and to a lesser degree in gesture recognition (P < .05). There was no significant change in performance on identifying body poses or in subjective assessments of mobility, as compared with a control group.ConclusionsConsumer AR devices may soon be able to support applications that improve the functional vision of users for some tasks. In our study, both artificially impaired participants and participants with near-complete vision loss performed tasks that they could not do without the AR system. Current limitations in system performance and form factor, as well as the risk of overconfidence, will need to be overcome.

People make surprising but reliable perceptual errors. Here, we provide a unified explanation for systematic errors in the perception of three-dimensional (3-D) motion. To do so, we characterized the binocular retinal motion signals produced by objects moving through arbitrary locations in 3-D. Next, we developed a Bayesian model, treating 3-D motion perception as optimal inference given sensory noise in the measurement of retinal motion. The model predicts a set of systematic perceptual errors, which depend on stimulus distance, contrast, and eccentricity. We then used a virtual-reality headset as well as a standard 3-D desktop stereoscopic display to test these predictions in a series of perceptual experiments. As predicted, we found evidence that errors in 3-D motion perception depend on the contrast, viewing distance, and eccentricity of a stimulus. These errors include a lateral bias in perceived motion direction and a surprising tendency to misreport approaching motion as receding and vice versa. In sum, we present a Bayesian model that provides a parsimonious account for a range of systematic misperceptions of motion in naturalistic environments.

People make surprising but reliable perceptual errors. Here, we provide a unified explanation for systematic errors in the perception of three-dimensional (3-D) motion. To do so, we characterized the binocular retinal motion signals produced by objects moving through arbitrary locations in 3-D. Next, we developed a Bayesian model, treating 3-D motion perception as optimal inference given sensory noise in the measurement of retinal motion. The model predicts a set of systematic perceptual errors, which depend on stimulus distance, contrast, and eccentricity. We then used a virtual-reality headset as well as a standard 3-D desktop stereoscopic display to test these predictions in a series of perceptual experiments. As predicted, we found evidence that errors in 3-D motion perception depend on the contrast, viewing distance, and eccentricity of a stimulus. These errors include a lateral bias in perceived motion direction and a surprising tendency to misreport approaching motion as receding and vice versa. In sum, we present a Bayesian model that provides a parsimonious account for a range of systematic misperceptions of motion in naturalistic environments.

From the desktop to the laptop to the mobile device, personal computing platforms evolve over time. Moving forward, wearable computing is widely expected to be integral to consumer electronics and beyond. The primary interface between a wearable computer and a user is often a near-eye display. However, current generation near-eye displays suffer from multiple limitations: they are unable to provide fully natural visual cues and comfortable viewing experiences for all users. At their core, many of the issues with near-eye displays are caused by limitations in conventional optics. Current displays cannot reproduce the changes in focus that accompany natural vision, and they cannot support users with uncorrected refractive errors. With two prototype near-eye displays, we show how these issues can be overcome using display modes that adapt to the user via computational optics. By using focus-tunable lenses, mechanically actuated displays, and mobile gaze-tracking technology, these displays can be tailored to correct common refractive errors and provide natural focus cues by dynamically updating the system based on where a user looks in a virtual scene. Indeed, the opportunities afforded by recent advances in computational optics open up the possibility of creating a computing platform in which some users may experience better quality vision in the virtual world than in the real one.

From the desktop to the laptop to the mobile device, personal computing platforms evolve over time. Moving forward, wearable computing is widely expected to be integral to consumer electronics and beyond. The primary interface between a wearable computer and a user is often a near-eye display. However, current generation near-eye displays suffer from multiple limitations: they are unable to provide fully natural visual cues and comfortable viewing experiences for all users. At their core, many of the issues with near-eye displays are caused by limitations in conventional optics. Current displays cannot reproduce the changes in focus that accompany natural vision, and they cannot support users with uncorrected refractive errors. With two prototype near-eye displays, we show how these issues can be overcome using display modes that adapt to the user via computational optics. By using focus-tunable lenses, mechanically actuated displays, and mobile gaze-tracking technology, these displays can be tailored to correct common refractive errors and provide natural focus cues by dynamically updating the system based on where a user looks in a virtual scene. Indeed, the opportunities afforded by recent advances in computational optics open up the possibility of creating a computing platform in which some users may experience better quality vision in the virtual world than in the real one.

Blur from defocus can be both useful and detrimental for visual perception: It can be useful as a source of depth information and detrimental because it degrades image quality. We examined these aspects of blur by measuring the natural statistics of defocus blur across the visual field. Participants wore an eye-and-scene tracker that measured gaze direction, pupil diameter, and scene distances as they performed everyday tasks. We found that blur magnitude increases with increasing eccentricity. There is a vertical gradient in the distances that generate defocus blur: Blur below the fovea is generally due to scene points nearer than fixation; blur above the fovea is mostly due to points farther than fixation. There is no systematic horizontal gradient. Large blurs are generally caused by points farther rather than nearer than fixation. Consistent with the statistics, participants in a perceptual experiment perceived vertical blur gradients as slanted top-back whereas horizontal gradients were perceived equally as left-back and right-back. The tendency for people to see sharp as near and blurred as far is also consistent with the observed statistics. We calculated how many observations will be perceived as unsharp and found that perceptible blur is rare. Finally, we found that eye shape in ground-dwelling animals conforms to that required to put likely distances in best focus.

Sensory systems are faced with an essentially infinite number of possible environmental events but have limited processing resources. Posed with this challenge, it makes sense to allocate these resources to prioritize the discrimination of events with the most behavioral relevance. Here, we asked if such relevance is reflected in the processing and perception of motion. We compared human performance on a rapid motion direction discrimination task, including monocular and binocular viewing. In particular, we determined sensitivity and bias for a binocular motion-in-depth (three-dimensional; 3D) stimulus and for its constituent monocular (two-dimensional; 2D) signals over a broad range of speeds. Consistent with prior work, we found that binocular 3D sensitivity was lower than monocular sensitivity for all speeds. Although overall sensitivity was worse for 3D discrimination, we found that the transformation from 2D to 3D motion processing also incorporated a pattern of potentially advantageous biases. One such bias is reflected by a criterion shift that occurs at the level of 3D motion processing and results in an increased hit rate for motion toward the head. We also observed an increase in sensitivity for 3D motion trajectories presented on crossed rather than uncrossed disparity pedestals, privileging motion trajectories closer to the observer. We used these measurements to determine the range of real-world trajectories for which rapid 3D motion discrimination is most useful. These results suggest that the neural mechanisms that underlie motion perception privilege behaviorally relevant motion and provide insights into the nature of human motion sensitivity in the real world.

Sensory systems are faced with an essentially infinite number of possible environmental events but have limited processing resources. Posed with this challenge, it makes sense to allocate these resources to prioritize the discrimination of events with the most behavioral relevance. Here, we asked if such relevance is reflected in the processing and perception of motion. We compared human performance on a rapid motion direction discrimination task, including monocular and binocular viewing. In particular, we determined sensitivity and bias for a binocular motion-in-depth (three-dimensional; 3D) stimulus and for its constituent monocular (two-dimensional; 2D) signals over a broad range of speeds. Consistent with prior work, we found that binocular 3D sensitivity was lower than monocular sensitivity for all speeds. Although overall sensitivity was worse for 3D discrimination, we found that the transformation from 2D to 3D motion processing also incorporated a pattern of potentially advantageous biases. One such bias is reflected by a criterion shift that occurs at the level of 3D motion processing and results in an increased hit rate for motion toward the head. We also observed an increase in sensitivity for 3D motion trajectories presented on crossed rather than uncrossed disparity pedestals, privileging motion trajectories closer to the observer. We used these measurements to determine the range of real-world trajectories for which rapid 3D motion discrimination is most useful. These results suggest that the neural mechanisms that underlie motion perception privilege behaviorally relevant motion and provide insights into the nature of human motion sensitivity in the real world.

Blur from defocus can be both useful and detrimental for visual perception: It can be useful as a source of depth information and detrimental because it degrades image quality. We examined these aspects of blur by measuring the natural statistics of defocus blur across the visual field. Participants wore an eye-and-scene tracker that measured gaze direction, pupil diameter, and scene distances as they performed everyday tasks. We found that blur magnitude increases with increasing eccentricity. There is a vertical gradient in the distances that generate defocus blur: Blur below the fovea is generally due to scene points nearer than fixation; blur above the fovea is mostly due to points farther than fixation. There is no systematic horizontal gradient. Large blurs are generally caused by points farther rather than nearer than fixation. Consistent with the statistics, participants in a perceptual experiment perceived vertical blur gradients as slanted top-back whereas horizontal gradients were perceived equally as left-back and right-back. The tendency for people to see sharp as near and blurred as far is also consistent with the observed statistics. We calculated how many observations will be perceived as unsharp and found that perceptible blur is rare. Finally, we found that eye shape in ground-dwelling animals conforms to that required to put likely distances in best focus.

Understanding the current status and historical trends of gender representation within a research field is an important component of fostering a diverse and inclusive scientific community. Here, we report on the gender representation of a large sample of the vision science research community--the attendees of the Annual Meeting of the Vision Sciences Society (VSS). Our analysis shows that the majority of scientists at all career levels in our sample are male. This imbalance is most pronounced for the senior scientists, whereas predoctoral students are nearly balanced between the genders. Historically, the gender imbalance was larger than it is at present, and it has followed a slow-but-steady trend toward gender parity over the past decade. A longitudinal analysis based on tracking individual attendees shows a larger dropout rate for female than male predoctoral trainees. However, among the trainees who continue in the vision science field after graduate school, evidence suggests that career advancement is quite similar between the genders. In an additional analysis, we found that the VSS Young Investigator awardees and the abstract review committee members reflect substantial gender imbalances, suggesting that these recognitions have yet to catch up with the greater gender balance of the rising generation of junior vision scientists. We hope that this report will encourage awareness of issues of diversity in the scientific community and further promote the development of a research field in which all talented scientists are supported to succeed.

Understanding the current status and historical trends of gender representation within a research field is an important component of fostering a diverse and inclusive scientific community. Here, we report on the gender representation of a large sample of the vision science research community--the attendees of the Annual Meeting of the Vision Sciences Society (VSS). Our analysis shows that the majority of scientists at all career levels in our sample are male. This imbalance is most pronounced for the senior scientists, whereas predoctoral students are nearly balanced between the genders. Historically, the gender imbalance was larger than it is at present, and it has followed a slow-but-steady trend toward gender parity over the past decade. A longitudinal analysis based on tracking individual attendees shows a larger dropout rate for female than male predoctoral trainees. However, among the trainees who continue in the vision science field after graduate school, evidence suggests that career advancement is quite similar between the genders. In an additional analysis, we found that the VSS Young Investigator awardees and the abstract review committee members reflect substantial gender imbalances, suggesting that these recognitions have yet to catch up with the greater gender balance of the rising generation of junior vision scientists. We hope that this report will encourage awareness of issues of diversity in the scientific community and further promote the development of a research field in which all talented scientists are supported to succeed.

Sighted animals must survive in an environment that is diverse yet highly structured. Neural-coding models predict that the visual system should allocate its computational resources to exploit regularities in the environment, and that this allocation should facilitate perceptual judgments. Here we use three approaches (natural scenes statistical analysis, a reanalysis of single-unit data from alert behaving macaque, and a behavioral experiment in humans) to address the question of how the visual system maximizes behavioral success by taking advantage of low-level regularities in the environment. An analysis of natural scene statistics reveals that the probability distributions for light increments and decrements are biased in a way that could be exploited by the visual system to estimate depth from relative luminance. A reanalysis of neurophysiology data from Samonds et al. (2012) shows that the previously reported joint tuning of V1 cells for relative luminance and binocular disparity is well matched to a predicted distribution of binocular disparities produced by natural scenes. Finally, we show that a percept of added depth can be elicited in images by exaggerating the correlation between luminance and depth. Together, the results from these three approaches provide further evidence that the visual system allocates its processing resources in a way that is driven by the statistics of the natural environment.

Sighted animals must survive in an environment that is diverse yet highly structured. Neural-coding models predict that the visual system should allocate its computational resources to exploit regularities in the environment, and that this allocation should facilitate perceptual judgments. Here we use three approaches (natural scenes statistical analysis, a reanalysis of single-unit data from alert behaving macaque, and a behavioral experiment in humans) to address the question of how the visual system maximizes behavioral success by taking advantage of low-level regularities in the environment. An analysis of natural scene statistics reveals that the probability distributions for light increments and decrements are biased in a way that could be exploited by the visual system to estimate depth from relative luminance. A reanalysis of neurophysiology data from Samonds et al. (2012) shows that the previously reported joint tuning of V1 cells for relative luminance and binocular disparity is well matched to a predicted distribution of binocular disparities produced by natural scenes. Finally, we show that a percept of added depth can be elicited in images by exaggerating the correlation between luminance and depth. Together, the results from these three approaches provide further evidence that the visual system allocates its processing resources in a way that is driven by the statistics of the natural environment.