Classification of Soft Biometric Traits When Matching Near-Infrared Long-Range Face Images Against Their Visible Counterparts

Narang, Neeru; Bourlai, Thirimachos

doi:10.1007/978-3-030-39489-9_5

Cited by 8 publications

(6 citation statements)

References 28 publications

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“…Replacing computational and communication platforms requires R&D adjustments related to existing checkpoint technologies. We refer to recent work on epidemicconditioned biometrics such as periocular face recognition (face around the eyes) [56], [98], [99], [100], mask detection [101], and adjusting e-interviewers with respect to the acoustic effects of mask wearing [102] and incorrect mask wearing [101], [103]. We also refer to [58], [104] for VOLUME 11, 2023 legal, ethical, and privacy concerns of the counter-epidemic checkpoint extension.…”

Section: ) Decentralization and Ssimentioning

confidence: 99%

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Post-Pandemic Follow-Up Audit of Security Checkpoints

et al. 2023

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This paper provides a follow-up audit of security checkpoints (or simply checkpoints) for mass transportation hubs such as airports and seaports aiming at the post-pandemic R&D adjustments. The goal of our study is to determine biometric-enabled resources of checkpoints for a counter-epidemic response. To achieve the follow-up audit goals, we embedded the checkpoint into the Emergency Management Cycle (EMC) -the core of any doctrine that challenges disaster. This embedding helps to identify the technologysocietal gaps between contemporary and post-pandemic checkpoints. Our study advocates a conceptual exploration of the problem using EMC profiling and formulates new tasks for checkpoints based on the COVID-19 pandemic lessons learned. In order to increase practical value, we chose a case study of face biometrics for an experimental post-pandemic follow-up audit. INDEX TERMSSecurity checkpoints, border control, mass-migration, follow-up audits, biometrics, counter-epidemic measures, post-pandemic, emergency management cycle, self-sovereign identity. NOMENCLATURE EMC Emergency Management Cycle. JHA Justice and Home Affairs. IR Infrared. R&D Research and Development. SSI Self-Sovereign Identity. Biosecurity Measures to mitigate the risks. of infectious diseases. Distributed ledger A database spreading across multiple sites or institutions. Vaccination passport A personal digital counter-epidemic certificate. Periocular biometric Area of a face around the eyes. The associate editor coordinating the review of this manuscript and approving it for publication was Vincenzo Conti .

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Section: ) Decentralization and Ssimentioning

confidence: 99%

“…There are several arguments in favour of this approach, in particular: (a) Cross-sensor periocular biometrics have been studied, in particular, in [98], [99], [100], and [114], and (b) IR face image is a useful source of features such as breathing function and air-breathing temperature.…”

Section: ) Goals and Approachmentioning

confidence: 99%

Post-Pandemic Follow-Up Audit of Security Checkpoints

et al. 2023

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“…There are several rational arguments for this approach: − The cross-sensor periocular biometrics have been studied, in particular, in [19], [20], [21], [25]; − Thermal or Infrared (IR) facial image has been used as a source of health-related indicators such as breathing function and air-breathing temperature [26]. We conducted the following experiments in order to achieve the above formulated goals (Fig.…”

Section: A Goals and Approachmentioning

confidence: 99%

“…Recent work on epidemic-conditioned biometrics focused on periocular biometrics (periocular is the face area around the eyes) [19], [20], [21], mask detection [23], and adjusting e-interviewers to the acoustic effects of mask wearing [24]. We also refer to [22] for legal, ethical, and privacy concerns of the counter-epidemic checkpoint extension.…”

Section: Introductionmentioning

confidence: 99%

Biometrics in the Time of Pandemic: 40% Masked Face Recognition Degradation can be Reduced to 2%

Queiroz¹,

Lai²,

Yanushkevich³

et al. 2022

Preprint

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In this study of the face recognition on masked versus unmasked faces generated using Flickr-Faces-HQ and SpeakingFaces datasets, we report 36.78% degradation of recognition performance caused by the mask-wearing at the time of pandemics, in particular, in border checkpoint scenarios. We have achieved better performance and reduced the degradation to 1.79% using advanced deep learning approaches in the crossspectral domain.

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“…In multi-modal systems soft traits can increase performance, and even using only soft traits for identification is possible [15], [16], but their most common use is for classification purposes [17]- [19]. A general system performing classification, instead of "enrolment and recongition" performs "training and classification", usually based on machine learning (ML) algorithms.…”

Section: Classification As a Mode Of Operationmentioning

confidence: 99%

Emerging Biometric Modalities and their Use: Loopholes in the Terminology of the GDPR and Resulting Privacy Risks

Bisztray

Gruschka

Bourlai

et al. 2021

2021 International Conference of the Biometrics Special Interest Group (BIOSIG)

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Technological advancements allow biometric applications to be more omnipresent than in any other time before. This paper argues that in the current EU data protection regulation, classification applications using biometric data receive less protection compared to biometric recognition. We analyse preconditions in the regulatory language and explore how this has the potential to be the source of unique privacy risks for processing operations classifying individuals based on soft traits like emotions. This can have high impact on personal freedoms and human rights and therefore, should be subject to data protection impact assessment.

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Classification of Soft Biometric Traits When Matching Near-Infrared Long-Range Face Images Against Their Visible Counterparts

Cited by 8 publications

References 28 publications

Post-Pandemic Follow-Up Audit of Security Checkpoints

Post-Pandemic Follow-Up Audit of Security Checkpoints

Biometrics in the Time of Pandemic: 40% Masked Face Recognition Degradation can be Reduced to 2%

Emerging Biometric Modalities and their Use: Loopholes in the Terminology of the GDPR and Resulting Privacy Risks

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