Year: 2025
Type: data-paper
Abstract: This manuscript presents a Pre-AttentiveGaze dataset. One of the defining characteristics of gaze-based authentication is the necessity for a rapid response. In this study, we constructed a dataset for identifying individuals through eye movements by inducing "pre-attentive processing" in response to a given gaze stimulus in a very short time. A total of 76,840 eye movement samples were collected from 34 participants across five sessions. From the dataset, we extracted the gaze features proposed in previous studies, pre-processed them, and validated the dataset by applying machine learning models. This study demonstrates the efficacy of the dataset and illustrates its potential for use in gaze-based authentication of visual stimuli that elicit pre-attentive processing.
Source: Scientific Data
Authors: Junryeol Jeon, Yeo-Gyeong Noh, JooYeong Kim, Jin-Hyuk Hong
Institution: Gwangju Institute of Science and Technology
Language: English
Subfield: Human-Computer Interaction
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,490
Awards: G1194156772, G6962897262, G95167297
OpenAlex ID: W4407483196