2023
DOI: 10.3390/s23031262
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Using Gaze for Behavioural Biometrics

Abstract: A principled approach to the analysis of eye movements for behavioural biometrics is laid down. The approach grounds in foraging theory, which provides a sound basis to capture the uniqueness of individual eye movement behaviour. We propose a composite Ornstein-Uhlenbeck process for quantifying the exploration/exploitation signature characterising the foraging eye behaviour. The relevant parameters of the composite model, inferred from eye-tracking data via Bayesian analysis, are shown to yield a suitable feat… Show more

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Cited by 3 publications
(3 citation statements)
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“…With respect to the analyses needed here such models are overly complex, given their aim of actually simulating gaze shifts, and/or just suitable to cope with simple visual stimuli. Thus, we draw to some extent on the approach proposed in [14] (recapped in Section 3.2), which provides a succinct phenomenological model of gaze behaviour adequate to our analyses.…”
Section: Methodsmentioning
confidence: 99%
“…With respect to the analyses needed here such models are overly complex, given their aim of actually simulating gaze shifts, and/or just suitable to cope with simple visual stimuli. Thus, we draw to some extent on the approach proposed in [14] (recapped in Section 3.2), which provides a succinct phenomenological model of gaze behaviour adequate to our analyses.…”
Section: Methodsmentioning
confidence: 99%
“…List of all biometric types to guide the literature search for biometrics. The following surveys were influential in identifying applicable biometrics [10,33,[44][45][46][47][48][49][50][51][52][53][54][55][56][57][58][59][60][61][62].…”
Section: Figurementioning
confidence: 99%
“…This dataset captures the eye movements of participants engaged in a series of diverse and dynamic tasks, including vergence, smooth pursuit, video viewing, self-paced reading, and random saccades, collectively referred to as ‘VRG’, ‘PUR’, ‘VID’, ‘TEX’, and ‘RAN’. These tasks encompass a wide range of stimuli and activities typical in VR environments, making the dataset an invaluable resource for our study [ 28 , 29 ].…”
Section: Introductionmentioning
confidence: 99%