An official website of the United States government
Emerging Virtual Reality (VR) displays with embedded eye trackers are currently becoming a commodity hardware (e.g., HTC Vive Pro Eye). Eye-tracking data can be utilized for several purposes, including gaze monitoring, privacy protection, and user authentication/identification. Identifying users is an integral part of many applications due to security and privacy concerns. In this paper, we explore methods and eye-tracking features that can be used to identify users. Prior VR researchers explored machine learning on motion-based data (such as body motion, head tracking, eye tracking, and hand tracking data) to identify users. Such systems usually require an explicit VR task and many features to train the machine learning model for user identification. We propose a system to identify users utilizing minimal eye-gaze-based features without designing any identification-specific tasks. We collected gaze data from an educational VR application and tested our system with two machine learning (ML) models, random forest (RF) and k-nearest-neighbors (kNN), and two deep learning (DL) models: convolutional neural networks (CNN) and long short-term memory (LSTM). Our results show that ML and DL models could identify users with over 98% accuracy with only six simple eye-gaze features. We discuss our results, their implications on security and privacy, and the limitations of our work.
more »
« less
Estimating Perceptual Depth Changes with Eye Vergence and Interpupillary Distance using an Eye Tracker in Virtual Reality
Virtual Reality (VR) technology has advanced to include eye-tracking, allowing novel research, such as investigating how our visual system coordinates eye movements with changes in perceptual depth. The purpose of this study was to examine whether eye tracking could track perceptual depth changes during a visual discrimination task. We derived two depth-dependent variables from eye tracker data: eye vergence angle (EVA) and interpupillary distance (IPD). As hypothesized, our results revealed that shifting gaze from near-to-far depth significantly decreased EVA and increased IPD, while the opposite pattern was observed while shifting from far-to-near. Importantly, the amount of change in these variables tracked closely with relative changes in perceptual depth, and supported the hypothesis that eye tracker data may be used to infer real-time changes in perceptual depth in VR. Our method could be used as a new tool to adaptively render information based on depth and improve the VR user experience.
more »
« less
- Award ID(s):
- 1937565
- PAR ID:
- 10390194
- Editor(s):
- Blascheck, Tanja; Bradshaw, Jessica; Vrzakova, Hana
- Date Published:
- Journal Name:
- ACM Symposium on Eye Tracking Research and Applications
- Page Range / eLocation ID:
- 1 to 7
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
As virtual reality (VR) garners more attention for eye tracking research, knowledge of accuracy and precision of head-mounted display (HMD) based eye trackers becomes increasingly necessary. It is tempting to rely on manufacturer-provided information about the accuracy and precision of an eye tracker. However, unless data is collected under ideal conditions, these values seldom align with on-site metrics. Therefore, best practices dictate that accuracy and precision should be measured and reported for each study. To address this issue, we provide a novel open-source suite for rigorously measuring accuracy and precision for use with a variety of HMD-based eye trackers. This tool is customizable without having to alter the source code, but changes to the code allow for further alteration. The outputs are available in real time and easy to interpret, making eye tracking with VR more approachable for all users.more » « less
-
Spatial ability is the ability to generate, store, retrieve, and transform visual information to mentally represent a space and make sense of it. This ability is a critical facet of human cognition that affects knowledge acquisition, productivity, and workplace safety. Although having improved spatial ability is essential for safely navigating and perceiving a space on earth, it is more critical in altered environments of other planets and deep space, which may pose extreme and unfamiliar visuospatial conditions. Such conditions may range from microgravity settings with the misalignment of body and visual axes to a lack of landmark objects that offer spatial cues to perceive size, distance, and speed. These altered visuospatial conditions may pose challenges to human spatial cognitive processing, which assists humans in locating objects in space, perceiving them visually, and comprehending spatial relationships between the objects and surroundings. The main goal of this paper is to examine if eye-tracking data of gaze pattern can indicate whether such altered conditions may demand more mental efforts and attention. The key dimensions of spatial ability (i.e., spatial visualization, spatial relations, and spatial orientation) are examined under the three simulated conditions: (1) aligned body and visual axes (control group); (2) statically misaligned body and visual axes (experiment group I); and dynamically misaligned body and visual axes (experiment group II). The three conditions were simulated in Virtual Reality (VR) using Unity 3D game engine. Participants were recruited from Texas A&M University student population who wore HTC VIVE Head-Mounted Displays (HMDs) equipped with eye-tracking technology to work on three spatial tests to measure spatial visualization, orientation, and relations. The Purdue Spatial Visualization Test: Rotations (PSVT: R), the Mental Cutting Test (MCT), and the Perspective Taking Ability (PTA) test were used to evaluate the spatial visualization, spatial relations, and spatial orientation of 78 participants, respectively. For each test, gaze data was collected through Tobii eye-tracker integrated in the HTC Vive HMDs. Quick eye movements, known as saccades, were identified by analyzing raw eye-tracking data using the rate of change of gaze position over time as a measure of mental effort. The results showed that the mean number of saccades in MCT and PSVT: R tests was statistically larger in experiment group II than in the control group or experiment group I. However, PTA test data did not meet the required assumptions to compare the mean number of saccades in the three groups. The results suggest that spatial relations and visualization may require more mental effort under dynamically misaligned idiotropic and visual axes than aligned or statically misaligned idiotropic and visual axes. However, the data could not reveal whether spatial orientation requires more/less mental effort under aligned, statically misaligned, and dynamically misaligned idiotropic and visual axes. The results of this study are important to understand how altered visuospatial conditions impact spatial cognition and how simulation- or game-based training tools can be developed to train people in adapting to extreme or altered work environments and working more productively and safely.more » « less
-
We introduce SearchGazer, a web-based eye tracker for remote web search studies using common webcams already present in laptops and some desktop computers. SearchGazer is a pure JavaScript library that infers the gaze behavior of searchers in real time. The eye tracking model self-calibrates by watching searchers interact with the search pages and trains a mapping of eye features to gaze locations and search page elements on the screen. Contrary to typical eye tracking studies in information retrieval, this approach does not require the purchase of any additional specialized equipment, and can be done remotely in a user's natural environment, leading to cheaper and easier visual attention studies. While SearchGazer is not intended to be as accurate as specialized eye trackers, it is able to replicate many of the research findings of three seminal information retrieval papers: two that used eye tracking devices, and one that used the mouse cursor as a restricted focus viewer. Charts and heatmaps from those original papers are plotted side-by-side with SearchGazer results. While the main results are similar, there are some notable differences, which we hypothesize derive from improvements in the latest ranking technologies used by current versions of search engines and diligence by remote users. As part of this paper, we also release SearchGazer as a library that can be integrated into any search page.more » « less
-
We describe the design and performance of a high-fidelity wearable head-, body-, and eye-tracking system that offers significant improvement over previous such devices. This device’s sensors include a binocular eye tracker, an RGB-D scene camera, a high-frame-rate scene camera, and two visual odometry sensors, for a total of ten cameras, which we synchronize and record from with a data rate of over 700 MB/s. The sensors are operated by a mini-PC optimized for fast data collection, and powered by a small battery pack. The device records a subject’s eye, head, and body positions, simultaneously with RGB and depth data from the subject’s visual environment, measured with high spatial and temporal resolution. The headset weighs only 1.4 kg, and the backpack with batteries 3.9 kg. The device can be comfortably worn by the subject, allowing a high degree of mobility. Together, this system overcomes many limitations of previous such systems, allowing high-fidelity characterization of the dynamics of natural vision.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1145/3517031.3529632
