An extensive study of user identification via eye movements across multiple datasets

Zaidawi, Sahar Mahdie Klim Al; Prinzler, Martin H. U.; Jonas, Lührs,; Maneth, Sebastian

doi:10.1016/j.image.2022.116804

Cited by 6 publications

(3 citation statements)

References 29 publications

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“…Albeit eye movements have been measured since the early 1900s, the event classification step conceals subtleties either at the conceptual level (how to define fixations and saccades) and at the algorithmic level that operationalises the previous (but for an in-depth discussion, the reader is urged to refer to Hessels et al [ 99 ]). Unfortunately, this issue is by and large overlooked in the biometric literature with few exceptions, e.g., [ 134 ] who devoted effort to analise the effect on final identification due to the widely adopted, baseline parameters, namely velocity threshold and minimum fixation duration. This attitude is somehow surprising, given the circumstances, as noted in Section 3 , that the vast majority of methods barely rely on saccade/fixation data.…”

Section: Discussionmentioning

confidence: 99%

Using Gaze for Behavioural Biometrics

D’Amelio

Patania

Buršić

et al. 2023

Sensors

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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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Section: Discussionmentioning

confidence: 99%

Using Gaze for Behavioural Biometrics

D’Amelio

Patania

Buršić

et al. 2023

Sensors

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“…In the I-VT algorithm, the velocity threshold for saccade detection was set to 45 deg./s, as in [ 55 ]. In addition, the minimum fixation duration threshold was determined at 55 ms [ 56 ].…”

Section: Methodsmentioning

confidence: 99%

eSEE-d: Emotional State Estimation Based on Eye-Tracking Dataset

et al. 2023

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Affective state estimation is a research field that has gained increased attention from the research community in the last decade. Two of the main catalysts for this are the advancement in the data analysis using artificial intelligence and the availability of high-quality video. Unfortunately, benchmarks and public datasets are limited, thus making the development of new methodologies and the implementation of comparative studies essential. The current work presents the eSEE-d database, which is a resource to be used for emotional State Estimation based on Eye-tracking data. Eye movements of 48 participants were recorded as they watched 10 emotion-evoking videos, each of them followed by a neutral video. Participants rated four emotions (tenderness, anger, disgust, sadness) on a scale from 0 to 10, which was later translated in terms of emotional arousal and valence levels. Furthermore, each participant filled three self-assessment questionnaires. An extensive analysis of the participants’ answers to the questionnaires’ self-assessment scores as well as their ratings during the experiments is presented. Moreover, eye and gaze features were extracted from the low-level eye-recorded metrics, and their correlations with the participants’ ratings are investigated. Finally, we take on the challenge to classify arousal and valence levels based solely on eye and gaze features, leading to promising results. In particular, the Deep Multilayer Perceptron (DMLP) network we developed achieved an accuracy of 92% in distinguishing positive valence from non-positive and 81% in distinguishing low arousal from medium arousal. The dataset is made publicly available.

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“…In such secondary iterations, information often needs to be recovered. Users often choose to change their actual needs due to the lack of functionality of the product, which results in the embarrassing situation of lost pain points and single-product functionality in the current market [31][32][33][34][35][36]. In the theoretical model of capability-demand, the sub-variables associated with it can be divided into four tiers: (1) user, (2) product function, (3) interaction environment, and (4) the most noteworthy tier of interaction links remains in the user and product function.…”

Section: From Competence Studies To Functional Pathways For Age-frien...mentioning

confidence: 99%

Reorganisation and Construction of an Age-Friendly Smart Recreational Home System: Based on Function–Capability Match Methodology

Zhou,

Huang,

Luo

et al. 2023

Applied Sciences

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Elderly users are unable to adapt to the technological dividend brought by the internet of everything as soon as possible due to the deterioration in cognitive and perceptual functions, especially in the state of development of modern intelligent homes whose users’ practical operational capabilities cannot be matched. This situation creates a digital divide in which older users also need helpmate intelligent home systems. Current research on innovative home systems often lacks a focus on the elderly and a matching mapping between smart homes and operational capabilities. Therefore, this study proposes a theoretical approach and model based on the matching between smart home functions and older users’ abilities. This modelling path provides specific guidance for actual smart home design practices. This study outlines the methodology, theoretical derivation, and construction of the user capability gradient for matching functions and requirements of elderly users. Based on a theoretical model, experimental data, and threshold law in practical application, the age-appropriate intelligent home control system is developed independently, and the integrated development of hardware and software cloud synergy is realised for the user pain points of elderly users to make up for the gap at this research level.

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An extensive study of user identification via eye movements across multiple datasets

Cited by 6 publications

References 29 publications

Using Gaze for Behavioural Biometrics

Using Gaze for Behavioural Biometrics

eSEE-d: Emotional State Estimation Based on Eye-Tracking Dataset

Reorganisation and Construction of an Age-Friendly Smart Recreational Home System: Based on Function–Capability Match Methodology

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