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LivDet2023 - Fingerprint liveness detection competition: advancing generalization

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  • Additional Information
    • Contributors:
      UAM. Departamento de Tecnología Electrónica y de las Comunicaciones
    • Publication Information:
      IEEE
    • Publication Date:
      2025
    • Collection:
      Universidad Autónoma de Madrid (UAM): Biblos-e Archivo
    • Abstract:
      The International Fingerprint Liveness Detection Competition (LivDet) is a biennial event that in-vites academic and industry participants to prove their advancements in Fingerprint Presentation Attack Detection (PAD). This edition, LivDet2023, proposed two challenges, “Liveness Detection in Action” and “Fingerprint Representation”, to evaluate the efficacy of PAD embedded in verifica-tion systems and the effectiveness and compactness of feature sets. A third, “hidden” challenge is the inclusion of two subsets in the training set whose sensor information is unknown, testing par-ticipants’ ability to generalize their models. Only bona fide fingerprint samples were provided to participants, and the competition reports and assesses the performance of their algorithms suffering from this limitation in data availability ; We would like to thank Dirk Morgeneier and his company Jenetric for sponsoring the LivDet 2023 competition. J.F. is supported by project BBforTAI (PID2021-127641OB-I00MICINN/FEDER)
    • File Description:
      application/pdf
    • Relation:
      2023 IEEE International Joint Conference on Biometrics (IJCB); https://doi.org/10.1109/IJCB57857.2023.10449291; September 25-28, 2023; Ljubljana (Slovenia); IEEE International Joint Conference on Biometrics (IJCB); Gobierno de España. PID2021-127641OB-I00; 2023 IEEE International Joint Conference on Biometrics (IJCB). 01 March 2024; http://hdl.handle.net/10486/718742
    • Accession Number:
      10.1109/IJCB57857.2023.10449291
    • Online Access:
      http://hdl.handle.net/10486/718742
      https://doi.org/10.1109/IJCB57857.2023.10449291
    • Rights:
      © 2023 IEEE ; openAccess
    • Accession Number:
      edsbas.6B855CBB