Summary
Challenges related to “on the move” biometrics are 1/ lower quality live biometric data, and 2/ no time to read the ePassport. Also, fully automatic biometric border control solutions, even with a stop allowed, are currently deployed only for pedestrians in controlled environments. Carmen innovates biometric solutions for non-stop border control, suitable for pedestrians and vehicles, in uncontrolled environmental conditions. Travellers’ authentication is achieved in two steps: 1) the biometric data (face, iris, periocular) of travellers is securely stored in their smartphones, thanks to a DTC (Digital Traveller Credential); 2) the biometric data is securely transferred from the DTC to the border authroity infrastructure, and compared to the live biometric data collected as the traveller crosses the border control point.
To address a variety of environmental conditions, Carmen uses both NIR and RGB live biometric images and compares them to the reference images that have been acquired with one type of lighting only. To make biometrics more robust, Carmen has a multimodal approach on face iris and periocular regions. In fraud detection, Carmen detects presentation attacks on moving travellers and detects anomalous traveller behaviour. To address small and large border crossing points, Carmen enables the use of fix and body-worn cameras. To address travellers in cars or lorries, Carmen detects face images in slowly moving vehicles, through the windows.
Travellers in coaches are controlled by border guards walking through the coach, using dedicated portable equipment as they walk.
Carmen addresses the robustness of DTC via data injection attacks. Carmen complies with the existing legal and ethical standards, and privacy is a central concern.
Carmen solutions will be demonstrated in operational conditions over the UK – France border, as French and UK border authorities are part of Carmen consortium, using the infrastructure proposed by the partner Brittany Ferries.
To address a variety of environmental conditions, Carmen uses both NIR and RGB live biometric images and compares them to the reference images that have been acquired with one type of lighting only. To make biometrics more robust, Carmen has a multimodal approach on face iris and periocular regions. In fraud detection, Carmen detects presentation attacks on moving travellers and detects anomalous traveller behaviour. To address small and large border crossing points, Carmen enables the use of fix and body-worn cameras. To address travellers in cars or lorries, Carmen detects face images in slowly moving vehicles, through the windows.
Travellers in coaches are controlled by border guards walking through the coach, using dedicated portable equipment as they walk.
Carmen addresses the robustness of DTC via data injection attacks. Carmen complies with the existing legal and ethical standards, and privacy is a central concern.
Carmen solutions will be demonstrated in operational conditions over the UK – France border, as French and UK border authorities are part of Carmen consortium, using the infrastructure proposed by the partner Brittany Ferries.
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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/101168325 |
| Start date: | 01-09-2024 |
| End date: | 31-08-2027 |
| Total budget - Public funding: | - 2 998 347,00 Euro |
Cordis data
Original description
Challenges related to “on the move” biometrics are 1/ lower quality live biometric data, and 2/ no time to read the ePassport. Also, fully automatic biometric border control solutions, even with a stop allowed, are currently deployed only for pedestrians in controlled environments. Carmen innovates biometric solutions for non-stop border control, suitable for pedestrians and vehicles, in uncontrolled environmental conditions. Travellers’ authentication is achieved in two steps: 1) the biometric data (face, iris, periocular) of travellers is securely stored in their smartphones, thanks to a DTC (Digital Traveller Credential); 2) the biometric data is securely transferred from the DTC to the border authroity infrastructure, and compared to the live biometric data collected as the traveller crosses the border control point.To address a variety of environmental conditions, Carmen uses both NIR and RGB live biometric images and compares them to the reference images that have been acquired with one type of lighting only. To make biometrics more robust, Carmen has a multimodal approach on face iris and periocular regions. In fraud detection, Carmen detects presentation attacks on moving travellers and detects anomalous traveller behaviour. To address small and large border crossing points, Carmen enables the use of fix and body-worn cameras. To address travellers in cars or lorries, Carmen detects face images in slowly moving vehicles, through the windows.
Travellers in coaches are controlled by border guards walking through the coach, using dedicated portable equipment as they walk.
Carmen addresses the robustness of DTC via data injection attacks. Carmen complies with the existing legal and ethical standards, and privacy is a central concern.
Carmen solutions will be demonstrated in operational conditions over the UK – France border, as French and UK border authorities are part of Carmen consortium, using the infrastructure proposed by the partner Brittany Ferries.
Status
SIGNEDCall topic
HORIZON-CL3-2023-BM-01-03Update Date
19-09-2024
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Organisations
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| YNCREA MEDITERRANEE (Coördinator)
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| ARCLAN'SYSTEM
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| B.A.I. BRETAGNE ANGLETERRE IRLANDE SA
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| CABINET LOUIS REYNAUD SASU
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| CIVI POL CONSEIL, SOCIETE DE CONSEIL ET DE SERVICE DU MINISTERE DE L'INTERIEUR
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| FONDATION DE L'INSTITUT DE RECHERCHE IDIAP (IDIAP)
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| HOCHSCHULE DARMSTADT (UNIVERSITY OF APPLIED SCIENCES H-DA)
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| HOME OFFICE
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| IDEMIA IDENTITY & SECURITY FRANCE (IDEMIA)
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| KENTRO MELETON ASFALEIAS
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| MINISTERE DE L'INTERIEUR
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| NOTITIA DOO ZA SAVJETOVANJE I USLUGE
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| THALES DIS FRANCE SAS
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| THE UNIVERSITY OF READING
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| YNCREA OUEST