Facial recognition application for border control

• Published in: 2018 International Joint Conference on Neural Networks (IJCNN) pp. 1 - 7
• Main Authors: Carlos-Roca, Laura Rodriguez, Torres, Isabelle Hupont, Tena, Carles Fernandez
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.07.2018
• Subjects: Biomedical imaging; Border control; facial recognition; deep learning; image analysis; Face; Face recognition; Logic gates; Machine learning; Security; Task analysis
• ISSN: 2161-4407
• DOI: 10.1109/IJCNN.2018.8489113

This paper provides an overview of border control processes and how the inclusion of different biometric technologies contributes to its improvement. In particular, facial recognition is one of the latest biometric technology to have been added to this list of technologies. The Face Matching Tool (FMT), a system defined to assist border guards in the process of validating the identity of a travel document holder during the crossing border process, is presented in this paper. The system is built using advanced and high-performance deep learning models. Existing solutions for border control, such as the Automated Border Check gates (ABC gates), are possible thanks to the use of facial recognition as the main option for identity validation. These solutions imply a decrease in the queue time that a traveler expends crossing the border at airports around the globe. The FMT module, together with the rest of the iBorderCtrl system, reduces this waiting time while providing unconstrained and high facial recognition performances at the land borders.