Facial biometrics for situational awareness systems

Poursaberi, Ahmad; Váňa, Jan; Mráček, Štěpán; Dvora, Radim; Yanushkevich, Svetlana; Drahanský, Martin; Shmerko, Vlad; Gavrilova, Marina L.

doi:10.1049/iet-bmt.2012.0065

Cited by 15 publications

(6 citation statements)

References 43 publications

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“…Other components include soft biometrics at a distance [39], [46], [47] and interview-supported machines with a virtual security officer [8], [9], [48]- [51]. Identifying pandemic features (geographical, as well as biometric measures such as temperature, blood pressure, and other features), traveler authentication is performed simultaneously.…”

Section: A Brief Overview Of Authentication Machine Applicationsmentioning

confidence: 99%

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Biometric-Enabled Authentication Machines: A Survey of Open-Set Real-World Applications

Eastwood

Shmerko

Yanushkevich

et al. 2016

IEEE Trans. Human-Mach. Syst.

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This paper revisits the concept of an authentication machine (A-machine) that aims at identifying/verifying humans. Although A-machines in the closed-set application scenario are well understood and commonly used for access control utilizing human biometrics (face, iris, and fingerprints), open-set applications of Amachines have yet to be equally characterized. This paper presents an analysis and taxonomy of A-machines, trends, and challenges of open-set real-world applications. This paper makes the following contributions to the area of open-set A-machines: 1) a survey of applications; 2) new novel life cycle metrics for theoretical, predicted, and operational performance evaluation; 3) a new concept of evidence accumulation for risk assessment; 4) new criteria for the comparison of A-machines based on the notion of a supporting assistant; and 5) a new approach to border personnel training based on the A-machine training mode. It offers a technique for modeling A-machines using belief (Bayesian) networks and provides an example of this technique for biometric-based e-profiling.

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Section: A Brief Overview Of Authentication Machine Applicationsmentioning

confidence: 99%

“…They enable some numerical estimations, but cannot provide all details necessary for feasible decision making. Some preliminary results on e-profiler design using biometrics and belief networks are given in [47] and [92].…”

Section: E-profilersmentioning

confidence: 99%

Biometric-Enabled Authentication Machines: A Survey of Open-Set Real-World Applications

Eastwood

Shmerko

Yanushkevich

et al. 2016

IEEE Trans. Human-Mach. Syst.

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“…Developers argue that only two or three cues at one time can be controlled by a human while being interrogated, but not all 15. The results of the experimental study of behavior biometrics for supporting the interview process are partially reported in [16].…”

Section: Brief Overview Of the Evolving Concept Of A-machinesmentioning

confidence: 99%

“…The results of the experimental study of behavior biometrics for supporting the interview process, such as [17], are reported in [16]. Examples of the behavior/risk analysis automated technology include the AVATAR machine [2], [14] and the FAST project [6].…”

Section: Definitionmentioning

confidence: 99%

Biometric Intelligence in Authentication Machines: from Talking Faces to Talking Robots

Eastwood

Shmerko

Yanushkevich

et al. 2014

2014 IIAI 3rd International Conference on Advanced Applied Informatics

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Biometric-based intelligence in authentication machines (A-machines) concerns with the problem of balancing human and machine functions in applications such as mass public events and border crossing. The focus of this paper is intelligent human-machine interfacing of behavior biometrics, which seems to play an important role in future generations of A-machines. Various pilot projects use the "talking face" technology. We suggest further improvement to A-machines based on "talking robot" technology: while interviewing the traveler, a humanoid robot recognizes faces and expressions, verifies the e-passports and the traveler (using his/her biometrics), connects with a watchlist (database), generates cognitive questions and analyzes answers, as well as detects soft biometric features in visual and infrared spectrum bands, such as temperature and blood pressure. Various parts of such technology have been implemented, and the feasibility of assembling such a multifunctional system in the form of a robot is to be studied and understood. This paper presents a survey of the related work, and also provides the authors' vision of future generations of A-machines and their applications.

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“…Biometric fusion can be performed at the data level, feature level, match score level, or decision level [2], [6]. Recent methods emphasize enhancing multimodal biometric systems performance.…”

Section: Introductionmentioning

confidence: 99%

Score-Level Fusion of Face and Voice Using Particle Swarm Optimization and Belief Functions

Mezai

Hachouf

2015

IEEE Trans. Human-Mach. Syst.

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We propose an efficient particle swarm optimization (PSO) technique that weights the belief assignments of voice and face classifiers. The belief assignment is computed from the score of each modality using Denoeux and Appriou models. The fusion of the weighted belief assignments is then performed by using Dempster-Shafer (DS) theory and proportional conflict redistribution (PCR5) combination rules. Experiments are conducted on the scores of XM2VTS and BANCA multimodal databases. A comparative study is achieved using our method, several existing PSObased fusion techniques, DS theory, and PCR5 combination rules. Experimental studies show that the proposed approach improves the error equal rate compared with the well-established methods on BANCA multimodal database since it contains controlled, degraded, and adverse data.Index Terms-Belief assignments, Dempster-Shafer (DS) theory, face, fusion, particle swarm optimization (PSO), proportional conflict redistribution, voice.

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Facial biometrics for situational awareness systems

Cited by 15 publications

References 43 publications

Biometric-Enabled Authentication Machines: A Survey of Open-Set Real-World Applications

Biometric-Enabled Authentication Machines: A Survey of Open-Set Real-World Applications

Biometric Intelligence in Authentication Machines: from Talking Faces to Talking Robots

Score-Level Fusion of Face and Voice Using Particle Swarm Optimization and Belief Functions

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