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Bibliographic Details
Main Authors: Qiu, Chuhui, Liang, Bugao, Key, Matthew L
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2408.03478
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Table of Contents:
  • In this paper, we present an algorithm of gaze prediction from Electroencephalography (EEG) data. EEG-based gaze prediction is a new research topic that can serve as an alternative to traditional video-based eye-tracking. Compared to the existing state-of-the-art (SOTA) method, we improved the root mean-squared-error of EEG-based gaze prediction to 53.06 millimeters, while reducing the training time to less than 33% of its original duration. Our source code can be found at https://github.com/AmCh-Q/CSCI6907Project