School of Information Science and Engineering, Shandong Normal University, Jinan 250399, China.
School of Journalism and Communication, Shandong Normal University, Jinan 250399, China.
Sensors (Basel). 2022 Apr 14;22(8):3002. doi: 10.3390/s22083002.
Eye movement has become a new behavioral feature for biometric authentication. In the eye movement-based authentication methods that use temporal features and artificial design features, the required duration of eye movement recordings are too long to be applied. Therefore, this study aims at using eye movement recordings with shorter duration to realize authentication. And we give out a reasonable eye movement recording duration that should be less than 12 s, referring to the changing pattern of the deviation degree between the gaze point and the stimulus point on the screen. In this study, the temporal motion features of the gaze points and the spatial distribution features of the saccade are using to represent the personal identity. Two datasets are constructed for the experiments, including 5 s and 12 s of eye movement recordings. On the datasets constructed in this paper, the open-set authentication results show that the Equal Error Rate of our proposed methods can reach 10.62% when recording duration is 12 s and 12.48% when recording duration is 5 s. The closed-set authentication results show that the Equal Error Rate of our proposed methods can reach 5.25% when recording duration is 12 s and 7.82% when recording duration is 5 s. It demonstrates that the proposed method provides a reference for the eye movements data-based identity authentication.
眼动已成为生物特征认证的一个新的行为特征。在使用时间特征和人工设计特征的眼动认证方法中,眼动记录所需的持续时间过长,难以应用。因此,本研究旨在使用持续时间更短的眼动记录来实现认证。我们给出了一个合理的眼动记录持续时间,应少于 12 秒,这是参考注视点和屏幕上刺激点之间的偏差程度的变化模式得出的。在这项研究中,我们使用注视点的时间运动特征和扫视的空间分布特征来表示个人身份。我们构建了两个数据集进行实验,包括 5 秒和 12 秒的眼动记录。在本文构建的数据集上,对于开放集认证结果,当记录持续时间为 12 秒时,我们提出的方法的等错误率可以达到 10.62%,当记录持续时间为 5 秒时,等错误率可以达到 12.48%。对于闭集认证结果,当记录持续时间为 12 秒时,我们提出的方法的等错误率可以达到 5.25%,当记录持续时间为 5 秒时,等错误率可以达到 7.82%。这表明所提出的方法为基于眼动数据的身份认证提供了参考。