Ocular Biometrics Recognition by Analyzing Human Exploration during Video Observations
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 s...
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| Published in | Applied sciences Vol. 10; no. 13; p. 4548 |
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| Main Authors | , , , , , |
| Format | Journal Article |
| Language | English |
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MDPI AG
01.07.2020
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| Online Access | Get full text |
| ISSN | 2076-3417 2076-3417 |
| DOI | 10.3390/app10134548 |
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| Abstract | 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. |
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| AbstractList | 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. 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. Keywords: soft biometrics; human attention recognition; gaze estimation; public gaze dataset |
| Audience | Academic |
| Author | Cazzato, Dario Cimarelli, Claudio Voos, Holger Carcagnì, Pierluigi Distante, Cosimo Leo, Marco |
| Author_xml | – sequence: 1 givenname: Dario orcidid: 0000-0002-5472-9150 surname: Cazzato fullname: Cazzato, Dario – sequence: 2 givenname: Pierluigi surname: Carcagnì fullname: Carcagnì, Pierluigi – sequence: 3 givenname: Claudio surname: Cimarelli fullname: Cimarelli, Claudio – sequence: 4 givenname: Holger surname: Voos fullname: Voos, Holger – sequence: 5 givenname: Cosimo surname: Distante fullname: Distante, Cosimo – sequence: 6 givenname: Marco orcidid: 0000-0001-5636-6130 surname: Leo fullname: Leo, Marco |
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| SubjectTerms | Analysis Attention Biometry Forecasts and trends Gaze gaze estimation human attention recognition Methods Optical properties public gaze dataset soft biometrics |
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| Title | Ocular Biometrics Recognition by Analyzing Human Exploration during Video Observations |
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