# GazeSync: A Mobile Eye-Tracking Tool for Analyzing Visual Attention on Dynamically Manipulated Content

arXiv: https://arxiv.org/abs/2604.15348 · HTML: https://mlsanity.com/paper/2604.15348/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 30 Mar 2026.

## Built on by (most cited first, 1 of 1)

- [Factor-Informed Uncertainty Distillation for Gaze Estimation](https://mlsanity.com/paper/2607.20072/) (2026)

## Abstract (arXiv)

Conventional mobile eye-tracking maps gaze to static screen coordinates, failing to capture user attention when content is dynamic. As users pinch, zoom, and rotate images, static coordinates lose their semantic meaning relative to the underlying visual content. To address this methodological gap, we present textitGazeSync, a reusable mobile system that synchronizes on-device gaze estimation with real-time image transformation matrices (scale, rotation, and translation). By logging gaze coordinates alongside precise UI states, GazeSync enables the accurate reconstruction of textitimage-relative attention patterns, decoupling visual attention from device interaction. We validate our end-to-end toolchain through a formative study involving guided manipulation, reading, and visual search tasks. Our results demonstrate GazeSync's ability to recover ground-truth gaze locations on transforming content, explicitly showing how it outperforms static baselines, while also surfacing critical boundaries regarding calibration drift and reconstruction fragility under compound manipulations.