Fusion of multiple clues for photo-attack detection in face recognition systems

Tronci, Roberto; Muntoni, Daniele; Fadda, Gianluca; Pili, Maurizio; Sirena, N.; Murgia, Gabriele; Ristori, Marco; Ricerche, Sardegna; Roli, Fabio

doi:10.1109/ijcb.2011.6117522

Cited by 66 publications

(50 citation statements)

References 9 publications

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“…A recent trend that came into prominence with [28], [26] involves combining several methods at score or feature level. The best results are achieved if the fused methods use complementary features which discern spoofing attacks from different aspects [29].…”

Section: Related Workmentioning

confidence: 99%

On the Use of Client Identity Information for Face Antispoofing

Chingovska

Anjos

2015

IEEE Trans.Inform.Forensic Secur.

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With biometrics playing the role of a password which can not be replaced if stolen, the necessity of establishing countermeasures to biometric spoofing attacks has been recognized. Regardless of the biometric mode, the typical approach of anti-spoofing systems is to classify biometric evidence based on features discriminating between real accesses and spoofing attacks. For the first time, to the best of our knowledge, this paper studies the amount of client-specific information within these features and how it affects the performance of anti-spoofing systems. We make use of this information to build two client-specific anti-spoofing solutions, one relying on a generative and another one on a discriminative paradigm. The proposed methods, tested on a set of state-of-the-art antispoofing features for the face mode, outperform the clientindependent approaches with up to 50% relative improvement and exhibit better generalization capabilities on unseen types of spoofing attacks.

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Section: Related Workmentioning

confidence: 99%

On the Use of Client Identity Information for Face Antispoofing

Chingovska

Anjos

2015

IEEE Trans.Inform.Forensic Secur.

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“…It requires computation of a weight parameter via majority voting [21]. In the second combination stage the team introduced a heuristic to exclude single frames with outlier scores.…”

Section: Summaries Of the Anti-spoofing Algorithmsmentioning

confidence: 99%

The 2nd competition on counter measures to 2D face spoofing attacks

Chingovska

Yang

Lei

et al. 2013

2013 International Conference on Biometrics (ICB)

100

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Esta es la versión de autor de la comunicación de congreso publicada en: This is an author produced version of a paper published in: AbstractAs a crucial security problem, anti-spoofing in biometrics, and particularly for the face modality, has achieved great progress in the recent years. Still, new threats arrive in form of better, more realistic and more sophisticated spoofing attacks. The objective of the 2nd Competition on Counter Measures to 2D Face Spoofing Attacks is to challenge researchers to create counter measures effectively detecting a variety of attacks. The submitted propositions are evaluated on the Replay-Attack database and the achieved results are presented in this paper.

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“…He demonstrated Bayesian fusion approach based on mutual dependency models for joint analysis of acoustic and visual speech features for liveness detection. Same author has also addressed the liveness checking scheme using multimodal fuzzy fusion in [24] by designing a mutual dependency modals which extract the spatio-temporal correlation between face and voice dynamics during speech generation.…”

Section: Multimodal Spoofing Detectionmentioning

confidence: 99%

“…R.Tronci et al [24] performed both static and dynamic analysis in order to detect complementary information about motion, texture and liveness. They extracted the problem of 2D face spoofing attacks detection as combination of several clues.…”

Section: Multimodal Spoofing Detectionmentioning

confidence: 99%