Modeling eye gaze velocity trajectories using GANs with spectral loss for enhanced fidelity

Modeling eye gaze velocity trajectories using GANs with spectral loss for enhanced fidelity

Abstract Accurate modeling of eye gaze dynamics is essential for advancement in human-computer interaction, neurological diagnostics, and cognitive research. Traditional generative models like Markov models often fail to capture the complex temporal dependencies and distributional nuance inherent in...

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Main Authors: Shailendra Bhandari, Pedro Lencastre, Rujeena Mathema, Alexander Szorkovszky, Anis Yazidi, Pedro G. Lind
Format: Article
Language:English
Published: Nature Portfolio 2025-06-01
Series:Scientific Reports
Subjects:
Generative Adversarial Networks
Stochastic Processes
Hidden Markov Models
Eye-gaze trajectories
Online Access:https://doi.org/10.1038/s41598-025-05286-5
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https://doi.org/10.1038/s41598-025-05286-5

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