Real masks and spoof faces: On the masked face presentation attack detection

Fang, Meiling; Damer, Naser; Kirchbuchner, Florian; Kuijper, Arjan

doi:10.1016/j.patcog.2021.108398

Cited by 48 publications

(19 citation statements)

References 34 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, the correlation between IQ and FIQ measures is relatively low, indicating that, as proven previously on bona fide samples in [34], an image with low perceptual quality does not necessarily lead to a low FR utility and vise versa. A clear example of that is applying FR on masked faces [11], [30], where an image of a masked face can be of high perceptual quality, but it is of low utility given the mask occlusion [36].…”

Section: Resultsmentioning

confidence: 99%

Face morphing attacks and face image quality: The effect of morphing and the unsupervised attack detection by quality

Damer

2022

IET Biometrics

Self Cite

View full text Add to dashboard Cite

Morphing attacks are a form of presentation attacks that gathered increasing attention in recent years. A morphed image can be successfully verified to multiple identities. This operation, therefore, poses serious security issues related to the ability of a travel or identity document to be verified to belong to multiple persons. Previous studies touched on the issue of the quality of morphing attack images, however, with the main goal of quantitatively proofing the realistic appearance of the produced morphing attacks. The authors theorise that the morphing processes might have an effect on both, the perceptual image quality and the image utility in face recognition (FR) when compared to bona fide samples. Towards investigating this theory, this work provides an extensive analysis of the effect of morphing on face image quality, including both general image quality measures and face image utility measures. This analysis is not limited to a single morphing technique but rather looks at six different morphing techniques and five different data sources using ten different quality measures. This analysis reveals consistent separability between the quality scores of morphing attack and bona fide samples measured by certain quality measures. The authors’ study goes further to build on this effect and investigate the possibility of performing unsupervised morphing attack detection (MAD) based on quality scores. The authors’ study looks into intra‐ and inter‐dataset detectability to evaluate the generalisability of such a detection concept on different morphing techniques and bona fide sources. The authors’ final results point out that a set of quality measures, such as MagFace and CNNIQA, can be used to perform unsupervised and generalised MAD with a correct classification accuracy of over 70%.

show abstract

Section: Resultsmentioning

confidence: 99%

Face morphing attacks and face image quality: The effect of morphing and the unsupervised attack detection by quality

Damer

2022

IET Biometrics

Self Cite

View full text Add to dashboard Cite

show abstract

“…Such software-based PAD for remote face and voice recognition were explored in the EU-H2020 TeSLA project [98]. It is expected that more research will be devoted to this topic in the future [99], [100].…”

Section: Security and Privacy In Remote Biometricsmentioning

confidence: 99%

Biometrics in the Era of COVID-19: Challenges and Opportunities

Gomez‐Barrero

Drozdowski

Rathgeb

et al. 2022

IEEE Trans. Technol. Soc.

Self Cite

View full text Add to dashboard Cite

Since early 2020, the COVID-19 pandemic has had a considerable impact on many aspects of daily life. A range of different measures have been implemented worldwide to reduce the rate of new infections and to manage the pressure on national health services. A primary strategy has been to reduce gatherings and the potential for transmission through the prioritisation of remote working and education. Enhanced hand hygiene and the use of facial masks have decreased the spread of pathogens when gatherings are unavoidable. These particular measures present challenges for reliable biometric recognition, e.g. for facial-, voiceand hand-based biometrics. At the same time, new challenges create new opportunities and research directions, e.g. renewed interest in non-constrained iris or periocular recognition, touchless fingerprint-and vein-based authentication and the use of biometric characteristics for disease detection. This article presents an overview of the research carried out to address those challenges and emerging opportunities.

show abstract

“…These findings led to a new direction in the FR research. Hence, an additional effort was made to solve the masked face recognition (MFR) problem, which benefit from contributions in the form of case-study papers [17,16,36,34], methods [28,25,29,4] and competitions [5,11]. Moreover, the effect of masks were not exclusively linked to recognition and studies can be found on their effect on face presentation attack detection methods [15,16].…”

Section: Introductionmentioning

confidence: 99%

“…Hence, an additional effort was made to solve the masked face recognition (MFR) problem, which benefit from contributions in the form of case-study papers [17,16,36,34], methods [28,25,29,4] and competitions [5,11]. Moreover, the effect of masks were not exclusively linked to recognition and studies can be found on their effect on face presentation attack detection methods [15,16]. The volume of new research led to a second part of the NIST FR vendor test, which evaluated the performance of FR algorithms designed post-covid [32].…”

Section: Introductionmentioning

confidence: 99%

OCFR 2022: Competition on Occluded Face Recognition From Synthetically Generated Structure-Aware Occlusions

Neto¹,

Pinto²,

Damer³

et al. 2022

Preprint

Self Cite

View full text Add to dashboard Cite

This work summarizes the IJCB Occluded Face Recognition Competition 2022 (IJCB-OCFR-2022) embraced by the 2022 International Joint Conference on Biometrics (IJCB 2022). OCFR-2022 attracted a total of 3 participating teams, from academia. Eventually, six valid submissions were submitted and then evaluated by the organizers. The competition was held to address the challenge of face recognition in the presence of severe face occlusions. The participants were free to use any training data and the testing data was built by the organisers by synthetically occluding parts of the face images using a well-known dataset. The submitted solutions presented innovations and performed very competitively with the considered baseline. A major output of this competition is a challenging, realistic, and diverse, and publicly available occluded face recognition benchmark with well defined evaluation protocols.

show abstract

Real masks and spoof faces: On the masked face presentation attack detection

Cited by 48 publications

References 34 publications

Face morphing attacks and face image quality: The effect of morphing and the unsupervised attack detection by quality

Face morphing attacks and face image quality: The effect of morphing and the unsupervised attack detection by quality

Biometrics in the Era of COVID-19: Challenges and Opportunities

OCFR 2022: Competition on Occluded Face Recognition From Synthetically Generated Structure-Aware Occlusions

Contact Info

Product

Resources

About