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GazeFS system enhances gaze interaction with trajectory forecasting

By PulseAugur Editorial · [1 sources] ·

Researchers have developed GazeFS, a novel system designed to improve target-centered gaze interaction by forecasting and stabilizing gaze trajectories. GazeFS analyzes gaze-head history to predict the next target direction and estimate search/focus states without needing explicit target information during inference. Experiments with 30 participants across thousands of acquisition episodes demonstrated that GazeFS significantly reduces bias, dispersion, and target error in gaze focus, outperforming raw gaze data and showing that historical gaze patterns contribute valuable information beyond explicit task progress. AI

IMPACT Improves precision in gaze-controlled interfaces, potentially enhancing accessibility and user experience in human-computer interaction.

RANK_REASON The item is a research paper published on arXiv detailing a new system and its experimental validation. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

GazeFS system enhances gaze interaction with trajectory forecasting

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The item is a research paper published on arXiv detailing a new system and its experimental validation. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Yaozheng Xia, Zaiping Zhu, Bo Pang, Minghao Xie, Hui Li, Shaorong Wang, Sheng Li ·

    GazeFS: Target-Centered Gaze-Trajectory Forecasting and Stabilization from Gaze-Head History

    arXiv:2609.03868v1 Announce Type: cross Abstract: Target-centered gaze interaction requires more than suppressing frame-to-frame fluctuations: target acquisition produces task-aligned changes in gaze-head dynamics, while a gaze trace may retain a persistent target-relative residu…

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