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Using Gaze for Behavioural Biometrics

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...

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Autores principales: D’Amelio, Alessandro, Patania, Sabrina, Bursic, Sathya, Cuculo, Vittorio, Boccignone, Giuseppe
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9920149/
https://www.ncbi.nlm.nih.gov/pubmed/36772302
http://dx.doi.org/10.3390/s23031262
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author D’Amelio, Alessandro
Patania, Sabrina
Bursic, Sathya
Cuculo, Vittorio
Boccignone, Giuseppe
author_facet D’Amelio, Alessandro
Patania, Sabrina
Bursic, Sathya
Cuculo, Vittorio
Boccignone, Giuseppe
author_sort D’Amelio, Alessandro
collection PubMed
description 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 feature set for biometric identification; the latter is eventually accomplished via a classical classification technique. A proof of concept of the method is provided by measuring its identification performance on a publicly available dataset. Data and code for reproducing the analyses are made available. Overall, we argue that the approach offers a fresh view on either the analyses of eye-tracking data and prospective applications in this field.
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spelling pubmed-99201492023-02-12 Using Gaze for Behavioural Biometrics D’Amelio, Alessandro Patania, Sabrina Bursic, Sathya Cuculo, Vittorio Boccignone, Giuseppe Sensors (Basel) Article 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 feature set for biometric identification; the latter is eventually accomplished via a classical classification technique. A proof of concept of the method is provided by measuring its identification performance on a publicly available dataset. Data and code for reproducing the analyses are made available. Overall, we argue that the approach offers a fresh view on either the analyses of eye-tracking data and prospective applications in this field. MDPI 2023-01-22 /pmc/articles/PMC9920149/ /pubmed/36772302 http://dx.doi.org/10.3390/s23031262 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
D’Amelio, Alessandro
Patania, Sabrina
Bursic, Sathya
Cuculo, Vittorio
Boccignone, Giuseppe
Using Gaze for Behavioural Biometrics
title Using Gaze for Behavioural Biometrics
title_full Using Gaze for Behavioural Biometrics
title_fullStr Using Gaze for Behavioural Biometrics
title_full_unstemmed Using Gaze for Behavioural Biometrics
title_short Using Gaze for Behavioural Biometrics
title_sort using gaze for behavioural biometrics
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9920149/
https://www.ncbi.nlm.nih.gov/pubmed/36772302
http://dx.doi.org/10.3390/s23031262
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