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'''Eye tracking''' is a technology that detects and analyzes [[eye movement]]s, [[gaze]] direction, and related metrics. In the context of [[virtual reality]] (VR) and [[augmented reality]] (AR), eye tracking enables headsets to determine precisely where users are looking, creating more immersive and efficient experiences. This technology has become increasingly important in modern [[head-mounted display]]s (HMDs), enabling advanced features like [[foveated rendering]], [[gaze-based interaction]], and enhanced user analytics.<ref>Duchowski, A. T. (2017). Eye Tracking Methodology: Theory and Practice. Springer.</ref>
{{see also|Terms|Technical Terms}}
[[Eye tracking]] is a sensor technology that measures [[eye]] positions and [[eye movement]]. In the context of [[virtual reality]] (VR) and [[augmented reality]] (AR), it refers to the integration of sensors within [[VR headset]]s or [[AR headset]]s to determine precisely where the user is looking ([[gaze]]) in real-time within the [[virtual environment]] or overlaid digital interface. By accurately monitoring characteristics like pupil position, corneal reflections, and eye movements such as [[saccades]] and fixations, this technology enables more immersive, efficient, and intuitive user experiences. It has become an increasingly critical feature in modern [[head-mounted display]]s ([[HMD]]s), driving advancements in rendering, interaction, analytics, and social presence.<ref name="Duchowski2017">Duchowski, A. T. (2017). *Eye Tracking Methodology: Theory and Practice*. Springer.</ref>


== Technical Principles ==
==History==
While its integration into consumer VR/AR is relatively recent, the systematic study of eye movements dates back to the 19th century. [[Louis Émile Javal]] noted in 1879 that reading involved discrete stops (fixations) and rapid movements (saccades).<ref name="Rayner1998">Rayner, K. (1998). Eye movements in reading and information processing: 20 years of research. *Psychological Bulletin, 124*(3), 372–422.</ref> Early tracking devices included [[Edmund Huey]]'s contact lens-based tracker (~1908)<ref name="Huey1908">Huey, E.B. (1908). *The Psychology and Pedagogy of Reading*. Macmillan.</ref> and [[Guy Thomas Buswell]]'s film-based systems in the 1930s. [[Alfred L. Yarbus]]'s work in the 1960s highlighted how viewing patterns are task-dependent.<ref name="Yarbus1967">Yarbus, A.L. (1967). *Eye Movements and Vision*. Plenum Press.</ref> These foundational efforts paved the way for modern video-based and integrated tracking systems.


=== Tracking Methods ===
==Technical Principles==
===Tracking Method===
Most eye tracking systems in contemporary VR and AR headsets employ one of several core technologies:


Most eye tracking systems in VR and AR employ one of several core technologies:
*'''[[Pupil Center Corneal Reflection]] (PCCR)''': This is the predominant method. It involves:<ref name="Holmqvist2011">Holmqvist, K., Nyström, M., Andersson, R., Dewhurst, R., Jarodzka, H., & Van de Weijer, J. (2011). *Eye tracking: A comprehensive guide to methods and measures*. Oxford University Press.</ref><ref name="RoadToVREyeTracking">Lang, B. (2021, July 21). *Casual Explainer: What is Eye-tracking & How Does it Work?* Road to VR. https://www.roadtovr.com/casual-explainer-what-is-eye-tracking-how-does-it-work/</ref>
*'''Illumination:''' [[Infrared]] (IR) light-emitting diodes ([[LED]]s) safely illuminate the eye. IR light is used because it is invisible to the human eye, preventing distraction, and provides high contrast for [[camera]]s.
*'''Imaging:''' Small, high-[[frame rate]] infrared cameras capture images of the eye, specifically tracking the center of the [[pupil]] and the reflection(s) of the IR light off the surface of the [[cornea]] (known as glints).
*'''[[Algorithm|Algorithmic Processing]]:''' Sophisticated [[computer vision]] and [[image processing]] algorithms analyze the captured images. By calculating the vector between the pupil center and the corneal reflection(s), the system determines the eye's orientation and calculates the user's gaze point with high accuracy.
*'''[[Calibration]]:''' A per-user calibration process is usually required upon first use, and sometimes periodically, to account for individual differences in eye physiology (for example corneal shape, pupil size range) and the precise fit of the headset. This typically involves the user looking at specific points displayed within the headset.


* '''Pupil Center Corneal Reflection (PCCR)''' - The most common method in modern headsets, which uses [[infrared light]] to create reflections on the cornea and tracks these reflections relative to the pupil center.<ref>Holmqvist, K., Nyström, M., Andersson, R., Dewhurst, R., Jarodzka, H., & Van de Weijer, J. (2011). Eye tracking: A comprehensive guide to methods and measures. Oxford University Press.</ref>
*'''Video-based eye tracking (Shape/Feature Tracking)''': Uses cameras aimed at the eyes to capture images, which are then analyzed using computer vision algorithms to identify eye features (pupil outline, iris texture, blood vessels) to determine gaze direction without necessarily relying on corneal reflections.<ref name="Hansen2010">Hansen, D. W., & Ji, Q. (2010). In the eye of the beholder: A survey of models for eyes and gaze. *IEEE Transactions on Pattern Analysis and Machine Intelligence, 32*(3), 478-500.</ref> PCCR is often considered a subset of this broader category.


* '''Video-based eye tracking''' - Uses small cameras aimed at the eyes to capture images that are then analyzed with [[computer vision]] algorithms to determine gaze direction.<ref>Hansen, D. W., & Ji, Q. (2010). In the eye of the beholder: A survey of models for eyes and gaze. IEEE Transactions on Pattern Analysis and Machine Intelligence, 32(3), 478-500.</ref>
*'''[[Electrooculography]] (EOG)''': Measures the electrical potential difference between electrodes placed on the skin around the eyes. This potential changes predictably as the eye rotates. While less common for high-accuracy gaze pointing in consumer VR/AR due to lower precision and susceptibility to muscle noise, it can be used for detecting larger eye movements or in specialized applications.<ref name="Bulling2011">Bulling, A., Ward, J. A., Gellersen, H., & Tröster, G. (2011). Eye movement analysis for activity recognition using electrooculography. *IEEE Transactions on Pattern Analysis and Machine Intelligence, 33*(4), 741-753.</ref>


* '''Electrooculography (EOG)''' - Measures the electrical potential between electrodes placed around the eye, which changes as the eye moves. Less common in VR/AR but useful in some specialized applications.<ref>Bulling, A., Ward, J. A., Gellersen, H., & Tröster, G. (2011). Eye movement analysis for activity recognition using electrooculography. IEEE Transactions on Pattern Analysis and Machine Intelligence, 33(4), 741-753.</ref>
*'''[[Scleral search coil]]''': Involves wearing a special contact lens containing a wire coil. The user sits within a magnetic field, and eye movements induce currents in the coil, providing extremely precise measurements. This is highly invasive and primarily used in laboratory research, not consumer VR/AR.<ref name="Robinson1963">Robinson, D.A. (1963). A method of measuring eye movement using a scleral search coil in a magnetic field. *IEEE Transactions on Biomedical Engineering, BME-10*(4), 137–145.</ref>


=== Key Components ===
===Key Components (PCCR-based)===
A typical PCCR eye tracking system integrated into a VR/AR headset consists of:
*'''Illuminators''': Infrared LEDs providing consistent, non-visible lighting.
*'''Cameras''': Specialized high-speed infrared cameras positioned to capture clear images of both eyes.
*'''Processing Unit''': Either onboard [[System on a Chip|SoC]] resources or dedicated hardware to run the detection and gaze calculation algorithms in real-time.
*'''Calibration Software''': [[Software]] routines guiding the user through calibration and storing individual profiles.<ref name="Kar2017">Kar, A., & Corcoran, P. (2017). A review and analysis of eye-gaze estimation systems, algorithms and performance evaluation methods in consumer platforms. *IEEE Access, 5*, 16495-16519.</ref>


A typical eye tracking system in VR/AR headsets consists of:
===Eye Movement Types Measured===
Eye tracking systems in VR/AR can detect and analyze various types of eye movements and states:
*'''[[Fixations]]''': Periods when the gaze remains relatively stable on a specific area (typically > 100-200 ms), indicating visual attention.
*'''[[Saccades]]''': Rapid, ballistic movements shifting the gaze between fixation points (typically 30-120 ms).
*'''[[Smooth pursuit]]''': Movements allowing the eyes to smoothly follow a moving object.
*'''[[Vergence]]''': The simultaneous movement of both eyes in opposite directions to obtain or maintain single binocular vision, critical for focusing on objects at different depths.
*'''[[Pupil dilation|Pupil Size / Dilation]]''': Changes in pupil diameter (pupillometry), which can correlate with changes in light levels, cognitive load, emotional arousal, or interest.<ref name="Leigh2015">Leigh, R. J., & Zee, D. S. (2015). *The neurology of eye movements*. Oxford University Press.</ref>
*'''Blinks''': Detection of eyelid closures.


* '''Illuminators''' - Usually infrared LEDs that provide consistent lighting without distracting the user
==Applications in VR and AR==
* '''Cameras''' - Specialized infrared cameras that capture eye images
Eye tracking unlocks numerous capabilities enhancing VR and AR experiences:
* '''Processing algorithms''' - Software that analyzes the captured images to determine eye position and movement
* '''Calibration system''' - Process to adjust the system to individual users' eye characteristics<ref>Kar, A., & Corcoran, P. (2017). A review and analysis of eye-gaze estimation systems, algorithms and performance evaluation methods in consumer platforms. IEEE Access, 5, 16495-16519.</ref>


=== Eye Movement Types ===
*'''[[Foveated rendering]]''': Arguably the most impactful application for performance. By knowing precisely where the user is looking, the system renders the scene at maximum [[resolution]] only in the small, central area of the user's gaze (corresponding to the eye's high-acuity fovea), while rendering the peripheral areas at progressively lower resolutions. This mimics human vision and can drastically reduce the computational load on the [[graphics processing unit]] (GPU) – potentially by 30% to over 70% – allowing for higher fidelity graphics, increased frame rates, reduced [[latency]], or lower power consumption, all without a noticeable loss in perceived visual quality.<ref name="Patney2016">Patney, A., Salvi, M., Kim, J., Kaplanyan, A., Wyman, C., Benty, N., Luebke, D., & Lefohn, A. (2016). Towards foveated rendering for gaze-tracked virtual reality. *ACM Transactions on Graphics, 35*(6), 179.</ref><ref name="TobiiFoveated">[https://www.tobii.com/blog/eye-tracking-in-vr-a-vital-component Tobii Blog: Eye Tracking in VR — A Vital Component]. Retrieved Nov 17, 2023.</ref><ref name="NvidiaFoveated">NVIDIA Corporation. (n.d.). *Maximize VR Performance with Foveated Rendering*. NVIDIA Developer. Retrieved November 16, 2023, from https://developer.nvidia.com/vrworks/graphics/foveatedrendering</ref>


Eye tracking systems in VR/AR can detect several types of eye movements:
*'''Natural Interaction / Gaze-Based Interaction''': Eye tracking enables more intuitive control schemes:
**'''Gaze Selection/Pointing''': Allows users to select objects, menu items, or targets simply by looking at them. This is often combined with a confirmation action like a button press on a [[controller (computing)|controller]], a [[hand tracking]] gesture (for example pinch), or a short dwell time.<ref name="Piumsomboon2017">Piumsomboon, T., Lee, G., Lindeman, R. W., & Billinghurst, M. (2017). Exploring natural eye-gaze-based interaction for immersive virtual reality. *IEEE Symposium on 3D User Interfaces*, 36-39.</ref>
**'''Intent Prediction''': Systems can anticipate user actions or needs based on gaze patterns (for example highlighting an object the user looks at intently).
**'''Gaze-directed Locomotion''': Steering movement within the virtual world based on gaze direction.


* '''[[Saccade]]s''' - Rapid movements between fixation points (30-80 ms)
*'''Enhanced Social Presence / [[Avatar]] Realism''': Realistic eye movements, including subtle saccades, blinks, and responsive gaze shifts, can be mirrored onto a user's avatar in social VR applications. This significantly enhances [[non-verbal communication]] and the feeling of [[social presence]] and connection when interacting with others.<ref name="MetaAvatarsEyeTracking">Meta Platforms, Inc. (2022, October 11). *Meta Quest Pro: A New Way to Work, Create and Collaborate*. Meta Quest Blog. https://www.meta.com/blog/quest/meta-quest-pro-vr-headset-features-price-release-date/</ref>
* '''Fixations''' - Relatively stable gazes on a specific area (200-300 ms)
* '''Smooth pursuits''' - Movements that track moving objects
* '''Vergence''' - Movements where eyes move in opposite directions to focus on objects at different depths
* '''Pupil dilation/constriction''' - Changes in pupil size which can indicate cognitive load or emotional response<ref>Leigh, R. J., & Zee, D. S. (2015). The neurology of eye movements. Oxford University Press.</ref>


== Applications in VR and AR ==
*'''User Analytics and Research''': Eye tracking provides invaluable objective data for:
**'''[[Usability testing]] & User Experience (UX) Research''': Understanding how users visually explore and interact with interfaces or environments.
**'''[[Attention mapping]]''': Creating heatmaps and gaze plots to visualize areas of interest and attention duration.
**'''Cognitive Load Assessment''': Measuring mental workload through metrics like pupil dilation, blink rate, and fixation patterns.<ref name="Clay2019">Clay, V., König, P., & König, S. (2019). Eye tracking in virtual reality. *Journal of Eye Movement Research, 12*(1).</ref>
**'''Training and Simulation Analysis''': Assessing trainee attention, situational awareness, and decision-making processes in professional simulations (for example medical, aviation).


=== Foveated Rendering ===
*'''Automatic [[Interpupillary distance|IPD]] Adjustment''': Some headsets utilize the eye tracking cameras to automatically measure the user's interpupillary distance (the distance between the centers of the pupils) and mechanically adjust the lens spacing for optimal visual clarity, stereo depth perception, and user comfort.


One of the most significant applications of eye tracking in VR/AR is [[foveated rendering]], a technique that renders images at full resolution only where the user is looking, while reducing detail in peripheral vision. This mimics the human visual system's natural function and can significantly reduce computational requirements.<ref>Patney, A., Salvi, M., Kim, J., Kaplanyan, A., Wyman, C., Benty, N., Luebke, D., & Lefohn, A. (2016). Towards foveated rendering for gaze-tracked virtual reality. ACM Transactions on Graphics, 35(6), 179.</ref>
*'''[[Accessibility]]''': Eye tracking offers a powerful hands-free input modality for users with limited physical mobility, enabling them to navigate interfaces, communicate (for example gaze typing), and control applications within VR/AR.


Benefits include:
*'''Adaptive Optics / [[Varifocal display]]s''': Eye tracking is essential for dynamic varifocal displays, which adjust their focal plane based on where the user is looking in virtual depth. This helps address the [[vergence-accommodation conflict]], potentially reducing eye strain and improving visual realism.<ref name="Akeley2004">Akeley, K., Watt, S.J., Girshick, A.R., & Banks, M.S. (2004). A stereo display prototype with multiple focal distances. *ACM Transactions on Graphics, 23*(3), 804–813.</ref>
* 30-60% reduction in GPU processing requirements
* Increased frame rates and reduced latency
* Ability to render more complex scenes
* Extended battery life in standalone headsets


=== Natural Interaction ===
*'''[[Dynamic Distortion Compensation]]''': Real-time adjustments to lens distortion correction based on precise eye position relative to the lens center can improve perceived sharpness across the field of view.<ref name="TobiiFoveated"/>


Eye tracking enables more intuitive ways to interact with virtual environments:
==Current Implementations==
Several commercially available VR and AR headsets incorporate integrated eye tracking:


* '''Gaze selection''' - Allows users to select objects simply by looking at them
===VR Headsets with Eye Tracking===
* '''Intent prediction''' - Systems can anticipate user actions based on gaze patterns
*'''[[Apple Vision Pro]]''': Uses high-precision eye tracking as a primary input method (combined with hand gestures and voice), enabling UI navigation, selection, and foveated rendering.<ref name="AppleVisionPro">Apple Inc. (n.d.). *Apple Vision Pro*. Apple. Retrieved November 16, 2023, from https://www.apple.com/apple-vision-pro/</ref>
* '''Social VR''' - Enables realistic [[avatar]] eye movements in virtual social interactions, greatly enhancing presence<ref>Piumsomboon, T., Lee, G., Lindeman, R. W., & Billinghurst, M. (2017). Exploring natural eye-gaze-based interaction for immersive virtual reality. IEEE Symposium on 3D User Interfaces, 36-39.</ref>
*'''[[Meta Quest Pro]]''': Features inward-facing sensors for eye and face tracking, primarily used for foveated rendering and driving realistic avatar expressions in social applications.<ref name="MetaAvatarsEyeTracking"/>
*'''[[PlayStation VR2]]''': Integrates [[Tobii]] eye tracking technology for foveated rendering, gaze-based interactions in games, and enhanced immersion.<ref name="SonyPSVR2">Sony Interactive Entertainment. (2023). *PS VR2 Features*. PlayStation.com. https://www.playstation.com/en-us/ps-vr2/features/</ref>
*'''[[HTC VIVE Pro Eye]]''': An earlier enterprise-focused headset integrating Tobii eye tracking (accuracy ~0.5-1.1 degrees, 120Hz). Newer VIVE models may offer eye tracking via add-ons (for example VIVE Focus 3 Eye Tracker).<ref name="ViveProEye">HTC Corporation. (n.d.). *VIVE Pro Eye*. VIVE. Retrieved November 16, 2023, from https://www.vive.com/us/product/vive-pro-eye/overview/</ref>
*'''[[Varjo]] XR-4, XR-3, VR-3, Aero''': High-end professional headsets featuring industrial-grade eye tracking (sub-degree accuracy, 200Hz) for demanding simulation, research, and design applications.<ref name="VarjoAero">Varjo Technologies Oy. (n.d.). *Varjo Aero*. Varjo. Retrieved November 16, 2023, from https://varjo.com/products/aero/</ref><ref name="VarjoXR3">Varjo Technologies. (2021). *Varjo XR-3 Technical Specifications*. Varjo.com.</ref>
*'''[[Pimax]] Crystal''': Consumer-focused high-resolution headset incorporating eye tracking for features like foveated rendering and automatic IPD adjustment.<ref name="PimaxCrystal">Pimax Technology (Shanghai) Co., Ltd. (n.d.). *Pimax Crystal*. Pimax. Retrieved November 16, 2023, from https://pimax.com/crystal/</ref>
*'''[[Pico 4 Enterprise]]''' (previously Pico Neo 3 Pro Eye): Enterprise headsets integrating Tobii eye tracking for business applications.<ref name="PicoNeo3Eye">Pico Interactive. (2021). *Pico Neo 3 Pro Eye Specifications*. Pico-interactive.com.</ref>
*'''[[HP Reverb G2 Omnicept Edition]]''': Featured integrated eye tracking (along with other biometric sensors) for enterprise use cases.<ref name="HPOmnicept">HP Development Company, L.P. (n.d.). *HP Reverb G2 Omnicept Edition VR Headset*. HP.com. Retrieved November 16, 2023, from https://www.hp.com/us-en/vr/reverb-g2-vr-headset-omnicept-edition.html</ref>


=== User Analytics and Research ===
===AR Headsets with Eye Tracking===
Eye tracking is also crucial for interaction and performance in AR:
*'''[[Microsoft HoloLens 2]]''': Uses eye tracking for user calibration, interaction (gaze targeting), and potentially performance optimization. Reported accuracy around 1.5 degrees.<ref name="HoloLens2">Microsoft Corporation. (2019). *HoloLens 2 Hardware Details*. Microsoft.com.</ref>
*'''[[Magic Leap 2]]''': Incorporates eye tracking for input (gaze, dwell), foveated rendering (on segmented dimmer), user calibration, and analytics.<ref name="MagicLeap2">Magic Leap, Inc. (2022). *Magic Leap 2 Technical Overview*. MagicLeap.com.</ref>


Eye tracking provides valuable data for:
==Technical Specifications and Performance Metrics==
===Key Performance Indicators===
The quality and usability of eye tracking systems are measured using several critical metrics:
*'''Accuracy''': The average difference between the true gaze point and the system's reported gaze point, typically measured in degrees of visual angle. Good systems achieve 0.5° to 1.5° accuracy within the central field of view.
*'''Precision''': The consistency or reproducibility of measurements for the same gaze point (RMS of successive samples). Often between 0.1° and 0.5°.
*'''Sampling Rate''': The frequency at which eye position is measured, expressed in Hertz (Hz). Consumer systems range from 30Hz to 120Hz or more, while research systems can exceed 1000Hz. Higher rates capture more detail about rapid movements like saccades.
*'''Latency''': The time delay between an actual eye movement and when it is detected and reported by the system. Crucial for real-time applications like foveated rendering and interaction, ideally below 20ms, though system latency can sometimes be higher (for example 45-81 ms reported in some studies).<ref name="SpringerReview2022">Mack, S., et al. (2022). A survey on eye tracking in virtual and augmented reality. *Virtual Reality*, 27, 1597–1625. https://link.springer.com/article/10.1007/s10055-022-00738-z</ref>
*'''Robustness / Tracking Ratio''': The percentage of time the system successfully tracks the eyes under various conditions (for example different users, lighting, eyewear).
*'''Field of View / Freedom of Head Movement''': The range of eye rotation and head position within which the system maintains tracking.
<ref name="Blignaut2018">Blignaut, P. (2018). Using eye tracking to assess user experience: A case of a mobile banking application. In *ACM International Conference Proceeding Series*, 219-228.</ref>


* '''User experience research''' - Understanding how users interact with virtual interfaces
===Calibration Methods===
* '''[[Attention mapping]]''' - Creating heatmaps of where users focus in virtual environments
Achieving specified accuracy typically requires individual user calibration:
* '''Cognitive load assessment''' - Measuring mental workload through pupil dilation and blink patterns
*'''Point Calibration''': The most common method. The user looks sequentially at several points displayed on the screen while the system records corresponding eye data to build a mapping model.
* '''Training and simulation''' - Analyzing trainee attention patterns in professional simulations<ref>Clay, V., König, P., & König, S. (2019). Eye tracking in virtual reality. Journal of Eye Movement Research, 12(1).</ref>
*'''Smooth Pursuit Calibration''': The user follows one or more moving targets across the screen.
*'''Implicit/Adjustment Calibration''': Systems that attempt to calibrate or refine calibration based on natural viewing behavior during normal use, potentially reducing user friction.
*'''Calibration Drift''': Accuracy can degrade over time due to headset slippage or physiological changes, potentially requiring recalibration. Some studies note significant drift (for example 30% accuracy loss) within minutes under certain conditions.<ref name="SpringerReview2022"/>
<ref name="Santini2018">Santini, T., Fuhl, W., & Kasneci, E. (2018). CalibMe: Fast and unsupervised eye tracker calibration for gaze-based pervasive human-computer interaction. *CHI Conference on Human Factors in Computing Systems*, 1-6.</ref>


=== Accessibility Features ===
==Challenges and Limitations==
Despite significant progress, eye tracking in VR/AR still faces hurdles:


Eye tracking enables VR/AR experiences for users with limited mobility:
===Technical Challenges===
*'''Individual Variations''': Differences in eye physiology (for example corneal curvature, pupil size, eyelid shape, ethnicity-related features, "droopy" eyelids) can impact tracking accuracy and robustness.
*'''Eyewear Compatibility''': Prescription glasses (especially with thick lenses, bifocals, or certain coatings) and some types of contact lenses can interfere with IR illumination and camera imaging, degrading performance.
*'''Processing Requirements''': Real-time, high-frequency eye tracking requires significant computational resources, impacting overall system performance and battery life, especially on standalone mobile headsets.
*'''Power Consumption''': The cameras and illuminators continuously consume power, contributing to battery drain in untethered devices.
*'''Accuracy/Latency Trade-offs''': Achieving both high accuracy and very low latency simultaneously remains challenging.
<ref name="Majaranta2014">Majaranta, P., & Bulling, A. (2014). Eye tracking and eye-based human-computer interaction. In *Advances in physiological computing*, 39-65. Springer.</ref>


* Hands-free navigation and control
===User Experience Concerns===
* Assistive communication through gaze typing
*'''Calibration Process''': The need for calibration can be perceived as inconvenient, especially if required frequently.
* Customized interfaces based on individual capabilities<ref>Yuan, Z., Bi, T., Muntean, G. M., & Ghinea, G. (2020). Perceived synchronization of mulsemedia services. IEEE Transactions on Multimedia, 17(7), 957-966.</ref>
*'''[[Privacy]] Implications''': Eye tracking data is highly sensitive [[biometric data]]. It can potentially reveal information about identity, attention focus, cognitive state, emotional responses, interests, and even certain health conditions (for example fatigue, intoxication, neurological disorders), raising significant privacy concerns if collected, stored, or shared improperly.<ref name="Kroger2020">Kröger, J. L., Lutz, O. H. M., & Müller, F. (2020). What does your gaze reveal about you? On the privacy implications of eye tracking. *Privacy and Identity Management*, 226-241.</ref><ref name="EFFPrivacyVRAR">Crockford, K., & Electronic Frontier Foundation. (2020, November 19). *The Privacy Bird Isn't Real: Your VR/AR Data Is*. Electronic Frontier Foundation. https://www.eff.org/deeplinks/2020/11/privacy-bird-isnt-real-your-vrar-data</ref>
*'''The "[[Uncanny Valley]]" Effect''': Imperfectly synchronized or unnatural avatar eye movements can appear disturbing rather than enhance social presence.


== Current Implementations ==
===Accessibility Issues===
*'''Compatibility with Eye Conditions''': Certain ophthalmological conditions (for example strabismus, nystagmus, ptosis, corneal scarring) can significantly impair or prevent accurate eye tracking for affected individuals.
*'''Make-up Interference''': Certain types of mascara or eyeliner can sometimes interfere with tracking.


=== VR Headsets with Eye Tracking ===
<ref name="Titz2018">Titz, J., Scholz, A., & Sedlmeier, P. (2018). Comparing eye trackers by correlating their eye-metric data. *Behavior Research Methods, 50*(5), 1853-1863.</ref>


Several commercial VR headsets now incorporate eye tracking:
==Future Developments==
The field continues to evolve rapidly:


* '''[[Apple Vision Pro]]''' - Uses high-precision eye tracking as a primary input method alongside hand tracking and voice commands. Features dual micro-OLED displays and includes eye tracking for both navigation and [[foveated rendering]].<ref>Apple Inc. (2023). Apple Vision Pro Technical Specifications. Apple.com.</ref>
===Emerging Technologies===
*'''Lower Power, Smaller Sensors''': Miniaturization and improved power efficiency for better integration into lighter HMDs.
*'''[[Artificial intelligence|AI]]/[[Machine learning|ML]]-Enhanced Tracking''': Using neural networks to improve robustness across diverse users, reduce calibration needs, and potentially infer more complex states from eye data.<ref name="Fuhl2016">Fuhl, W., Santini, T., Kasneci, G., & Kasneci, E. (2016). PupilNet: Convolutional neural networks for robust pupil detection. *CoRR, abs/1601.04902*.</ref>
*'''Advanced Optical Designs''': Novel lens and camera configurations to improve tracking quality, especially for users with eyewear.
*'''Sensor Fusion''': Combining eye tracking data with other sensor inputs (for example [[electroencephalography]] (EEG), head tracking, facial expression tracking) for richer interaction and analysis.


* '''[[HTC VIVE Pro Eye]]''' - Integrates Tobii eye tracking technology with accuracy of 0.5-1.1 degrees and a tracking frequency of 120Hz. Supports foveated rendering and gaze-based user interface interaction.<ref>HTC Corporation. (2019). VIVE Pro Eye User Guide. Vive.com.</ref>
===Research Directions===
*'''Predictive Tracking''': Algorithms that anticipate eye movements to compensate for system latency, enabling smoother foveated rendering and interaction.
*'''Emotion and Cognitive State Recognition''': Refining models to reliably infer affective states or cognitive load from eye metrics for adaptive interfaces or mental health applications.
*'''Standardization''': Developing common metrics, APIs, and data formats to facilitate cross-platform development and research comparison.
*'''Longitudinal Tracking''': Understanding how gaze patterns change over extended use and adapting systems accordingly.
<ref name="Duchowski2018">Duchowski, A. T., Krejtz, K., Krejtz, I., Biele, C., Niedzielska, A., Kiefer, P., Raubal, M., & Giannopoulos, I. (2018). The index of pupillary activity: Measuring cognitive load vis-à-vis task difficulty with pupil oscillation. *CHI Conference on Human Factors in Computing Systems*, 1-13.</ref>


* '''[[Varjo VR-3]]''' and '''[[Varjo XR-3]]''' - Feature industrial-grade eye tracking with sub-degree accuracy and a 200Hz tracking rate. Used primarily for professional applications such as training, simulation, and research.<ref>Varjo Technologies. (2021). Varjo VR-3 Technical Specifications. Varjo.com.</ref>
==Software Development and APIs==
Integrating eye tracking into applications requires specific software support:


* '''[[Pico Neo 3 Pro Eye]]''' - Incorporates Tobii eye tracking for enterprise applications with 90Hz refresh rate and 6DoF tracking.<ref>Pico Interactive. (2021). Pico Neo 3 Pro Eye Specifications. Pico-interactive.com.</ref>
===Development Frameworks and APIs===
*'''[[Unity (game engine)|Unity]]''': Provides APIs through its XR Interaction Toolkit and potential vendor-specific SDKs (for example Tobii XR SDK).
*'''[[Unreal Engine]]''': Offers native interfaces and plugins for accessing eye tracking data.
*'''[[OpenXR]]''': The cross-platform standard includes an `XR_EXT_eye_gaze_interaction` extension, allowing developers to write more portable code.
*'''Vendor SDKs''': Companies like [[Tobii]] provide dedicated Software Development Kits offering fine-grained control and optimized features for their hardware.<ref name="TobiiSDK">Tobii Technology. (2023). *Tobii XR SDK Documentation*. Tobii.com.</ref>


* '''[[Meta Quest Pro]]''' - Features internal and external sensors for face and eye tracking to facilitate more realistic avatars and social interactions.<ref>Meta. (2022). Meta Quest Pro Features and Specifications. Meta.com.</ref>
===Data Access Levels===
Developers typically access eye tracking data at different levels of abstraction:
*'''Raw Data''': Direct coordinates of pupil centers, glints, eye openness, etc. Requires significant processing by the application.
*'''Gaze Data''': Processed output providing calibrated gaze origin and direction vectors, or intersection points on virtual surfaces.
*'''Eye Movement Events''': Classified data identifying fixations, saccades, and blinks.
*'''Semantic Data''': Higher-level interpretations, such as the specific object being looked at (gaze target) or estimated attention levels.
<ref name="Kumar2016">Kumar, D., Dutta, A., Das, A., & Lahiri, U. (2016). SmartEye: Developing a novel eye tracking system for quantitative assessment of oculomotor abnormalities. *IEEE Transactions on Neural Systems and Rehabilitation Engineering, 24*(10), 1051-1059.</ref>


=== AR Headsets with Eye Tracking ===
==Ethical and Privacy Considerations==
The collection and use of eye tracking data necessitate careful ethical consideration:


Eye tracking is equally important in AR implementations:
*'''Biometric Data Privacy''': Gaze patterns can be unique identifiers. This data requires strong [[data security]] measures and compliance with regulations like [[GDPR]] (which may classify it as sensitive biometric data).
*'''Inference and Profiling''': The potential to infer sensitive information (health, emotions, interests) without explicit consent raises ethical questions.
*'''Attention Monitoring''': Concerns about workplace surveillance or manipulative advertising based on attention analytics.
*'''Informed Consent''': Users must be clearly informed about what eye data is collected, how it is processed, stored, and shared, and for what purposes. Opt-in mechanisms are crucial.
*'''Data Minimization and Anonymization''': Collect only necessary data, anonymize or aggregate whenever possible, and define clear data retention policies.
<ref name="Kroger2020"/>


* '''[[Microsoft HoloLens 2]]''' - Uses eye tracking for improved user interface interaction and application control with reported accuracy of about 1.5 degrees.<ref>Microsoft Corporation. (2019). HoloLens 2 Hardware Details. Microsoft.com.</ref>
==Standards and Regulations==
Efforts are underway to standardize aspects of eye tracking technology and address its implications:
*'''[[Khronos Group]] / [[OpenXR]]''': Defines standard APIs for accessing eye tracking data (for example [[XR_EXT_eye_gaze_interaction]]).
*'''[[IEEE Standards Association|IEEE]]''': Working groups like IEEE P2048.5 focus on standards for immersive learning, potentially including eye tracking metrics.
*'''[[Virtual Reality Industry Forum]] (VRIF)''': Develops guidelines for VR implementation, potentially covering eye tracking best practices.
*'''Data Protection Regulations''': [[GDPR]] (Europe), [[CCPA]]/[[CPRA]] (California), and similar laws globally impose requirements on handling personal and biometric data, including eye tracking data.
*'''[[ISO]]/[[IEC]] JTC 1/SC 24''': Committee working on international standards for computer graphics, image processing, and environmental data representation, relevant to VR/AR interfaces.<ref name="ISO_SC24">International Organization for Standardization. (2023). *ISO/IEC JTC 1/SC 24 - Computer graphics, image processing and environmental data representation*. ISO.org.</ref>


* '''[[Magic Leap 2]]''' - Incorporates eye tracking for interface control and developer analytics with a reported field of view of 70° diagonal.<ref>Magic Leap, Inc. (2022). Magic Leap 2 Technical Overview. MagicLeap.com.</ref>
==See Also==
*   [[Augmented reality]]
*  [[AR headset]]
*  [[Attention mapping]]
*  [[Avatar]]
*  [[Computer vision]]
*  [[Foveated rendering]]
*  [[Gaze]]
*  [[Hand tracking]]
*  [[Head-mounted display]]
*  [[Human eye]]
*  [[Human–computer interaction]]
*  [[Infrared]]
*  [[Interpupillary distance]]
*  [[Latency]]
*  [[Privacy]] in VR/AR
*  [[Pupil]]
*  [[Saccade]]
*  [[Social presence]]
*  [[Tobii]]
*  [[Varifocal display]]
*  [[Vergence-accommodation conflict]]
*  [[Virtual reality]]
*  [[VR headset]]


* '''[[Nreal Light]]''' - Features basic eye tracking capabilities for user interface interactions.<ref>Nreal. (2020). Nreal Light Technical Specifications. Nreal.io.</ref>
==References==
 
<references />
== Technical Specifications and Performance Metrics ==
 
=== Key Performance Indicators ===
 
The performance of eye tracking systems is measured using several critical metrics:
 
* '''Accuracy''' - Typically measured in degrees of visual angle, with industry standards ranging from 0.5° to 1.5°
* '''Precision''' - The consistency of measurements, usually between 0.1° and 0.5°
* '''Sampling rate''' - Frequency of eye position measurement, ranging from 30Hz in basic systems to 250Hz or higher in research-grade equipment
* '''Latency''' - Time delay between eye movement and system detection, ideally below 20ms for VR/AR applications
* '''Robustness''' - Performance across different users, lighting conditions, and use scenarios<ref>Blignaut, P. (2018). Using eye tracking to assess user experience: A case of a mobile banking application. In ACM International Conference Proceeding Series, 219-228.</ref>
 
=== Calibration Methods ===
 
Most eye tracking systems require calibration to achieve optimal performance:
 
* '''Point calibration''' - User looks at specific points on screen while the system measures eye positions
* '''Pursuit calibration''' - User follows moving targets
* '''Implicit calibration''' - System calibrates through normal use without specific user actions<ref>Santini, T., Fuhl, W., & Kasneci, E. (2018). CalibMe: Fast and unsupervised eye tracker calibration for gaze-based pervasive human-computer interaction. CHI Conference on Human Factors in Computing Systems, 1-6.</ref>
 
== Challenges and Limitations ==
 
Despite significant advances, eye tracking in VR/AR faces several challenges:
 
=== Technical Challenges ===
 
* '''Individual variations''' - Eye physiology differs significantly between users, affecting tracking accuracy
* '''Eyewear compatibility''' - Glasses and contact lenses can interfere with tracking systems
* '''Processing requirements''' - High-frequency eye tracking requires substantial computational resources
* '''Power consumption''' - A concern particularly for standalone and mobile devices<ref>Majaranta, P., & Bulling, A. (2014). Eye tracking and eye-based human-computer interaction. In Advances in physiological computing, 39-65. Springer.</ref>
 
=== User Experience Concerns ===
 
* '''Calibration fatigue''' - Frequent recalibration can frustrate users
* '''Privacy implications''' - Eye tracking data can reveal significant personal information
* '''The "Uncanny Valley" effect''' - If avatar eye movements aren't perfectly synchronized, they can appear disturbing<ref>Vrij, A., & Mann, S. (2020). Eye movements as a detection tool: a review and theoretical framework. Frontiers in Psychology, 11, 1538.</ref>
 
=== Accessibility Issues ===
 
* '''Compatibility with eye conditions''' - Users with strabismus, nystagmus, or other eye conditions may experience reduced tracking quality
* '''Cultural differences''' in eye movement patterns
* '''Age-related variations''' in pupil responsiveness and eye movement<ref>Titz, J., Scholz, A., & Sedlmeier, P. (2018). Comparing eye trackers by correlating their eye-metric data. Behavior Research Methods, 50(5), 1853-1863.</ref>
 
== Future Developments ==
 
The field of eye tracking in VR/AR continues to advance rapidly:
 
=== Emerging Technologies ===
 
* '''Micro LED-based trackers''' - Smaller, more power-efficient tracking systems
* '''Neural network approaches''' - AI-enhanced tracking that adapts to individual users
* '''Multispectral imaging''' - Using multiple light wavelengths for improved accuracy
* '''Non-visible light tracking''' - Advanced techniques that don't require infrared illumination<ref>Fuhl, W., Santini, T., Kasneci, G., & Kasneci, E. (2016). PupilNet: Convolutional neural networks for robust pupil detection. CoRR, abs/1601.04902.</ref>
 
=== Research Directions ===
 
* '''Combined eye-brain interfaces''' - Integrating eye tracking with [[electroencephalography]] (EEG) for enhanced interaction
* '''Emotion detection''' - Using pupil dilation and eye movement patterns to infer emotional states
* '''Predictive tracking''' - Algorithms that anticipate eye movements to reduce perceived latency
* '''Cross-platform standardization''' - Efforts to create universal eye tracking metrics and APIs<ref>Duchowski, A. T., Krejtz, K., Krejtz, I., Biele, C., Niedzielska, A., Kiefer, P., Raubal, M., & Giannopoulos, I. (2018). The index of pupillary activity: Measuring cognitive load vis-à-vis task difficulty with pupil oscillation. CHI Conference on Human Factors in Computing Systems, 1-13.</ref>
 
== Software Development and APIs ==
 
=== Development Frameworks ===
 
Several platforms offer tools for eye tracking integration:
 
* '''[[Unity XR Interaction Toolkit]]''' - Provides eye tracking input support for Unity developers
* '''[[Unreal Engine Eye Tracking Interface]]''' - API for implementing eye tracking in Unreal Engine applications
* '''[[OpenXR]]''' - Offers eye tracking extension for cross-platform development
* '''[[Tobii XR SDK]]''' - Specialized development kit for Tobii eye tracking hardware<ref>Tobii Technology. (2022). Tobii XR SDK Documentation. Tobii.com.</ref>
 
=== Data Processing Approaches ===
 
Developers can access eye tracking data at various levels:
 
* '''Raw data''' - Direct access to eye position coordinates and pupil measurements
* '''Filtered data''' - Processed data with noise reduction and classification of eye movements
* '''Semantic data''' - High-level interpretation of gaze targets and user attention<ref>Kumar, D., Dutta, A., Das, A., & Lahiri, U. (2016). SmartEye: Developing a novel eye tracking system for quantitative assessment of oculomotor abnormalities. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 24(10), 1051-1059.</ref>
 
== Ethical and Privacy Considerations ==
 
The powerful nature of eye tracking creates important ethical considerations:
 
* '''Biometric data protection''' - Eye tracking can create unique biometric signatures requiring appropriate safeguards
* '''Attention analytics''' - The potential for monitoring user attention raises privacy concerns
* '''Informed consent''' - Users should understand what eye data is collected and how it's used
* '''Data minimization''' - Only necessary eye tracking data should be collected and stored<ref>Kröger, J. L., Lutz, O. H. M., & Müller, F. (2020). What does your gaze reveal about you? On the privacy implications of eye tracking. Privacy and Identity Management, 226-241.</ref>
 
== Standards and Regulations ==
 
Several organizations work on standardizing eye tracking technology:
 
* '''[[IEEE P2048.5]]''' - Working group on eye tracking for VR/AR
* '''[[VRIF Guidelines]]''' - Virtual Reality Industry Forum guidelines for eye tracking implementation
* '''[[GDPR]]''' implications for eye tracking data in Europe
* '''[[ISO/IEC JTC 1/SC 24]]''' - International standards for VR/AR interfaces including eye tracking<ref>International Organization for Standardization. (2021). ISO/IEC JTC 1/SC 24 - Computer graphics, image processing and environmental data representation. ISO.org.</ref>
 
== References ==
<references/>
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