The technology behind IRIS-XR

The technology behind IRIS-XR

IRIS-XR combines breakthrough advances in displays,sensing technologies, and AI-driven interaction to createmore immersive, responsive, and human-centred XRexperiences

Shaping the Future of XR

Advanced XR display technology visualization

Sharper visuals.
Greater immersion.
Lower energy consumption.

Expected Improvements

  • Up to 10x reduction in halo effects
  • Higher contrast and image uniformity
  • Expanded colour gamut
  • Up to 50% lower backlight power consumption
Pillar 1

Advanced XR Display Technology

Visual quality is a fundamental requirement for professional XR applications. However, current display technologies often suffer from limited contrast, visible artefacts, reduced colour fidelity, and high power consumption.

IRIS-XR is developing a new generation of XR displays based on advanced mini/micro-LED backlight technology with intelligent local dimming capabilities. This approach significantly improves visual realism while reducing energy consumption and enhancing user comfort during extended sessions.

Ultra-fast eye and gesture tracking visualization

Understanding users with
unprecedented precision,
speed, and reliability.

Expected Improvements

  • Display-integrated NIR illumination with a compact optical design
  • Eye tracking latency below 5 ms
  • Sampling rates above 1 kHz
  • More than 40% reduction in sensing power consumption
Pillar 2

Ultra-Fast Eye and Gesture Tracking

Interaction is at the heart of every immersive experience. Yet existing XR systems often struggle with latency, environmental sensitivity, limited accuracy, and high power requirements.

IRIS-XR introduces a novel sensing architecture based on SPAES (Single Photon Active Event Sensing) technology and display-integrated near-infrared (NIR) illumination. By embedding NIR LEDs directly into the display, the system delivers enhanced illumination within a smaller form factor, improving eye-tracking accuracy while reducing optical complexity. Combined with event-driven sensing, this approach captures only relevant information, dramatically increasing efficiency and responsiveness.

AI-driven multimodal interaction visualization

Adaptive XR experiences
that understand users
and respond in real time.

Expected Improvements

  • Multimodal interaction latency below 10 ms
  • More than 50% reduction in tracking drift
  • Local AI processing with no cloud dependency
  • Adaptive user-specific interaction models
Pillar 3

AI-Driven Multimodal Interaction

Most current XR systems process eye movements, gestures, and spatial information separately, limiting their ability to adapt dynamically to users and environments.

IRIS-XR develops an advanced AI-driven interaction framework capable of fusing gaze, gesture, and depth information in real time. This multimodal approach creates a more natural, robust, and personalised interaction model.

Human-centred and trustworthy XR

Beyond technological excellence, IRIS-XR places strong emphasis on ethics, inclusiveness, accessibility, privacy, and user trust.

GDPR compliance
AI Act readiness
Accessibility requirements
Inclusive design principles
Safety-by-design methodologies
Responsible XR deployment

Three innovation pillars.
One integrated XR ecosystem.

  • Mini/Micro-LED Backlights
  • Enhanced Contrast
  • Reduced Halo Effects
  • Lower Energy Consumption
  • Greater Visual Comfort
  • SPAES Event-Based Sensors
  • Ultra-Fast Eye Tracking
  • Gesture Recognition
  • Sub-10 ms Latency
  • Outdoor Robustness
  • AI Multimodal Fusion
  • Real-Time Adaptation
  • Drift Compensation
  • Personalised Experiences
  • Privacy-Preserving AI

From Innovation to Impact

The technologies developed within IRIS-XR will be validated through three real-world pilots in mental healthcare, aviation training, and automotive design. These demonstrations will showcase how advanced XR technologies can improve accessibility, performance, safety, and collaboration across diverse professional and societal domains.

Discover the pilots

Stay connected with IRIS-XR

This project has received funding from the European Union’s Horizon Europe research and innovation programme under grant agreement N° 101298672. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or European Union’s Horizon Europe research and innovation programme. Neither the European Union nor the granting authority can be held responsible for them.

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