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New diffusion model synthesizes high-frequency gaze data for biometrics

By PulseAugur Editorial · [1 sources] ·

Researchers have developed EyeMakeYou, a novel diffusion model designed to synthesize high-frequency gaze data for eye movement biometrics. This model conditions gaze generation on identity, task, and subjective states like tiredness, aiming to create more realistic and behaviorally relevant synthetic data than previous methods. Experiments on the GazeBase dataset demonstrated EyeMakeYou's superior performance in spatial accuracy and feature-space similarity compared to existing generative approaches, supporting its utility for augmenting gaze datasets in biometric and interactive applications. AI

IMPACT This model could significantly improve the development and robustness of eye movement biometrics by addressing data scarcity with realistic synthetic gaze sequences.

RANK_REASON The cluster contains an academic paper detailing a new generative model for synthesizing gaze data. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CV →

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

New diffusion model synthesizes high-frequency gaze data for biometrics

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The cluster contains an academic paper detailing a new generative model for synthesizing gaze data. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CV TIER_1 English(EN) · Kamrul Hasan, Mehedi Hasan Raju, Oleg V. Komogortsev ·

    EyeMakeYou: Identity-, Task-, and Subjective-State-Conditioned Diffusion for High-Frequency Gaze Synthesis

    arXiv:2609.04501v1 Announce Type: cross Abstract: Eye movement biometrics (EMB) is an emerging behavioral modality for user authentication, particularly in virtual- and augmented-reality systems, where gaze dynamics contain distinctive subject-specific features. However, robust E…

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