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cs.HC2026
Gaze Prediction as Time-Series Forecasting for Virtual Reality Applications: Quantifying Performance Variability and Extreme-Case Errors
Kateryna Melnyk, Lee Friedman, Oleg Komogortsev
Gaze prediction is essential for addressing motion-to-photon latency and ensuring seamless foveated rendering in Virtual Reality. The reliability of gaze forecasting is highly sens…
cs.HC2025
Gaze Prediction as a Function of Eye Movement Type and Individual Differences
Kateryna Melnyk, Lee Friedman, Dmytro Katrychuk +1
Eye movement prediction is a promising area of research with the potential to improve performance and the user experience of systems based on eye-tracking technology. In this study…
cs.HC2024
Signal vs Noise in Eye-tracking Data: Biometric Implications and Identity Information Across Frequencies
Mehedi H. Raju, Lee Friedman, Dillon Lohr +1
Prior research states that frequencies below 75 Hz in eye-tracking data represent the primary eye movement termed ``signal'' while those above 75 Hz are deemed ``noise''. This stud…