# Evaluating Cross-Subject and Cross-Device Consistency in Visual Fixation Prediction

arXiv: https://arxiv.org/abs/2502.05554 · HTML: https://mlsanity.com/paper/2502.05554/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 8 Feb 2025.

## Built on by (most cited first, 2 of 2)

- [Raising the Ceiling: Better Empirical Fixation Densities for Saliency Benchmarking](https://mlsanity.com/paper/2605.03885/) (2026)
- [Consensus Clustering of Free-Viewing Gaze Data: New Insights into Human-Information Interaction](https://mlsanity.com/paper/2606.30035/) (2026)

## Abstract (arXiv)

Understanding cross-subject and cross-device consistency in visual fixation prediction is essential for advancing eye-tracking applications, including visual attention modeling and neuroprosthetics. This study evaluates fixation consistency using an embedded eye tracker integrated into regular-sized glasses, comparing its performance with high-end standalone eye-tracking systems. Nine participants viewed 300 images from the MIT1003 dataset in subjective experiments, allowing us to analyze cross-device and cross-subject variations in fixation patterns with various evaluation metrics. Our findings indicate that average visual fixations can be reliably transferred across devices for relatively simple stimuli. However, individual-to-average consistency remains weak, highlighting the challenges of predicting individual fixations across devices. These results provide an empirical foundation for leveraging predicted average visual fixation data to enhance neuroprosthetic applications.