# iTrace: Click-Based Gaze Visualization on the Apple Vision Pro

arXiv: https://arxiv.org/abs/2508.12268 · HTML: https://mlsanity.com/paper/2508.12268/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 5 of its 28 references that are in the map.
- First posted on arXiv 17 Aug 2025.

## Builds on (most cited first, 5 of 5)

- [Mobile Augmented Reality: User Interfaces, Frameworks, and Intelligence](https://mlsanity.com/paper/2106.08710/) (2021)
- [A Comprehensive Review of Multimodal XR Applications, Risks, and Ethical Challenges in the Metaverse](https://mlsanity.com/paper/2411.04508/) (2024)
- [Measuring eye-tracking accuracy and its impact on usability in apple vision pro](https://mlsanity.com/paper/2406.00255/) (2024)
- [A First Look at Immersive Telepresence on Apple Vision Pro](https://mlsanity.com/paper/2405.10422/) (2024)
- [Virtual Reality User Interface Design: Best Practices and Implementation](https://mlsanity.com/paper/2508.09358/) (2025)

## Abstract (arXiv)

The Apple Vision Pro is equipped with accurate eye-tracking capabilities, yet the privacy restrictions on the device prevent direct access to continuous user gaze data. This study introduces iTrace, a novel application that overcomes these limitations through click-based gaze extraction techniques, including manual methods like a pinch gesture, and automatic approaches utilizing dwell control or a gaming controller. We developed a system with a client-server architecture that captures the gaze coordinates and transforms them into dynamic heatmaps for video and spatial eye tracking. The system can generate individual and averaged heatmaps, enabling analysis of personal and collective attention patterns. To demonstrate its effectiveness and evaluate the usability and performance, a study was conducted with two groups of 10 participants, each testing different clicking methods. The 8BitDo controller achieved higher average data collection rates at 14.22 clicks/s compared to 0.45 clicks/s with dwell control, enabling significantly denser heatmap visualizations. The resulting heatmaps reveal distinct attention patterns, including concentrated focus in lecture videos and broader scanning during problem-solving tasks. By allowing dynamic attention visualization while maintaining a high gaze precision of 91 %, iTrace demonstrates strong potential for a wide range of applications in educational content engagement, environmental design evaluation, marketing analysis, and clinical cognitive assessment. Despite the current gaze data restrictions on the Apple Vision Pro, we encourage developers to use iTrace only in research settings.