3 research outputs found
Iris Liveness Detection Competition (LivDet-Iris) -- The 2020 Edition
Launched in 2013, LivDet-Iris is an international competition series open to
academia and industry with the aim to assess and report advances in iris
Presentation Attack Detection (PAD). This paper presents results from the
fourth competition of the series: LivDet-Iris 2020. This year's competition
introduced several novel elements: (a) incorporated new types of attacks
(samples displayed on a screen, cadaver eyes and prosthetic eyes), (b)
initiated LivDet-Iris as an on-going effort, with a testing protocol available
now to everyone via the Biometrics Evaluation and Testing
(BEAT)(https://www.idiap.ch/software/beat/) open-source platform to facilitate
reproducibility and benchmarking of new algorithms continuously, and (c)
performance comparison of the submitted entries with three baseline methods
(offered by the University of Notre Dame and Michigan State University), and
three open-source iris PAD methods available in the public domain. The best
performing entry to the competition reported a weighted average APCER of
59.10\% and a BPCER of 0.46\% over all five attack types. This paper serves as
the latest evaluation of iris PAD on a large spectrum of presentation attack
instruments.Comment: 9 pages, 3 figures, 3 tables, Accepted for presentation at
International Joint Conference on Biometrics (IJCB 2020
Iris Liveness Detection Competition (LivDet-Iris) – The 2020 Edition
Launched in 2013, LivDet-Iris is an international competition series open to academia and industry with the aim to assess and report advances in iris Presentation Attack Detection (PAD). This paper presents results from the fourth competition of the series: LivDet-Iris 2020. This year's competition introduced several novel elements: (a) incorporated new types of attacks (samples displayed on a screen, cadaver eyes and prosthetic eyes), (b) initiated LivDet-Iris as an on-going effort, with a testing protocol available now to everyone via the Biometrics Evaluation and Testing (BEAT)open-source platform to facilitate reproducibility and benchmarking of new algorithms continuously, and (c) performance comparison of the submitted entries with three baseline methods (offered by the University of Notre Dame and Michigan State University), and three open-source iris PAD methods available in the public domain. The best performing entry to the competition reported a weighted average APCER of 59.10% and a BPCER of 0.46% over all five attack types. This paper serves as the latest evaluation of iris PAD on a large spectrum of presentation attack instruments
Face Liveness Detection Competition (LivDet-Face) - 2021
Liveness Detection (LivDet)-Face is an international competition series open to academia and industry. The competition’s objective is to assess and report state-of-the-art in liveness / Presentation Attack Detection (PAD) for face recognition. Impersonation and presentation of false samples to the sensors can be classified as presentation attacks and the ability for the sensors to detect such attempts is known as PAD. LivDet-Face 2021 * will be the first edition of the face liveness competition. This competition serves as an important benchmark in face presentation attack detection, offering (a) an independent assessment of the current state of the art in face PAD, and (b) a common evaluation protocol, availability of Presentation Attack Instruments (PAI) and live face image dataset through the Biometric Evaluation and Testing (BEAT) platform. The competition can be easily followed by researchers after it is closed, in a platform in which participants can compare their solutions against the LivDet-Face winners