Reference : Ocular Biometrics Recognition by Analyzing Human Exploration during Video Observations
Scientific journals : Article
Engineering, computing & technology : Computer science
Security, Reliability and Trust
http://hdl.handle.net/10993/45559
Ocular Biometrics Recognition by Analyzing Human Exploration during Video Observations
English
Cazzato, Dario []
Carcagni, Pierluigi []
Cimarelli, Claudio [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > Automation >]
Voos, Holger mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > Automation >]
Distante, Cosimo []
Leo, Marco []
30-Jun-2020
Applied Sciences
MDPI AG
10
13
4548
Yes
International
2076-3417
Switzerland
[en] Ocular Biometrics Recognition ; Computer Vision
[en] Soft biometrics provide information about the individual but without the distinctiveness and permanence able to discriminate between any two individuals. Since the gaze represents one of the most investigated human traits, works evaluating the feasibility of considering it as a possible additional soft biometric trait have been recently appeared in the literature. Unfortunately, there is a lack of systematic studies on clinically approved stimuli to provide evidence of the correlation between exploratory paths and individual identities in “natural” scenarios (without calibration, imposed constraints, wearable tools). To overcome these drawbacks, this paper analyzes gaze patterns by using a computer vision based pipeline in order to prove the correlation between visual exploration and user identity. This correlation is robustly computed in a free exploration scenario, not biased by wearable devices nor constrained to a prior personalized calibration. Provided stimuli have been designed by clinical experts and then they allow better analysis of human exploration behaviors. In addition, the paper introduces a novel public dataset that provides, for the first time, images framing the faces of the involved subjects instead of only their gaze tracks.
http://hdl.handle.net/10993/45559
10.3390/app10134548
https://www.mdpi.com/2076-3417/10/13/4548

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