This work investigates gaze-based person identification using different stimuli and machine learning methods. The aim was to find out how different stimuli influence the accuracy of identification by eye movements. Using MATLAB and neural networks, the coordinates of each frame were extracted to perform person classification using a classification learner. 55 subjects participated in the study.
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Luce et al. (2024) studied this question.
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