Real-Time Face Detection and Motion Analysis With Application in “Liveness” Assessment

Kollreider, K.; Fronthaler, H.; Faraj, Maycel Isaac; Bigün, Josef

doi:10.1109/tifs.2007.902037

Cited by 254 publications

(111 citation statements)

References 25 publications

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“…In [2] swing Kollreider et.al proposed a facial anti-spoofing technique proposed is based on lip movement. Users are asked to start uttering the specific number sequence prompted randomly from 0 to 9 and each lip movement was recorded sequentially.…”

Section: A Face Anti-spoofingmentioning

confidence: 99%

An Intelligent Approach for Anti-Spoofing in a Multimodal Biometric System

Devakumar¹,

Sarala²

2017

IJARCSSE

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Abstract-Biometric systems are vulnerable to certain type of attacks at various points in the biometric model. A spoofing attack which is submitting a stolen, copied biometric trait to the sensor to gain unauthorized access to the biometric system is one among them. Multimodal biometric systems are designed to increase the accuracy of the biometric system, but they are more vulnerable to spoofing attacks than a unimodal biometric system. The existing approaches for anti-spoofing do not consider multiple biometric traits and also have a high false acceptance rate. The proposed method is designed to overcome spoofing in a multimodal biometric system that uses a combination of face, fingerprint and iris images. The extracted biometric features are fused and fed to a convolution neural network that employs deep learning to detect spoofed features from real features. The proposed method gives better results than existing anti-spoofing methods.

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Section: A Face Anti-spoofingmentioning

confidence: 99%

An Intelligent Approach for Anti-Spoofing in a Multimodal Biometric System

Devakumar¹,

Sarala²

2017

IJARCSSE

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“…Some methods use multi-spectral analysis [6], or response to a challenge which is posed to the user [7] to detect spoofing attacks. The mandatory additional hardware required alongside the biometric sensor is the primary drawback of the former approach, while the intrusiveness of the latter.…”

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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“…3D sensors may be influenced by computation, measurement time, expense and quality anticipated from estimation. represents a synopsis of distinctive sorts of procurement frameworks utilized as a part of the writing for face liveness discovery [5]. …”

Section: A) Sensormentioning

confidence: 99%

Applications of Client Identity Information for Face Antispoofing

2015

IJSR

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Lately, facial biometric frameworks have gotten expanded organization in different applications, for example, reconnaissance, access control and measurable examinations. On the other hand, one of the confinements of face antispoofing framework is the high probability of the framework being hoodwinked or mock by non-genuine faces, for example, photo, video clasps or sham countenances. With a specific end goal to recognize the caricaturing assaults on such biometric frameworks, face liveness discovery methodologies have been produced. Along these lines, the present methodology is to coordinate liveness recognition inside of facial biometrics by utilizing life sign markers of individual elements. This paper introduces a survey of best in class strategies in face liveness identification, which are arranged into two gatherings, to be specific meddlesome and non-nosy methodologies. Here, each strategy is talked about as far as its execution, qualities and impediments, and also signs on.

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Real-Time Face Detection and Motion Analysis With Application in “Liveness” Assessment

Cited by 254 publications

References 25 publications

An Intelligent Approach for Anti-Spoofing in a Multimodal Biometric System

An Intelligent Approach for Anti-Spoofing in a Multimodal Biometric System

On the Use of Client Identity Information for Face Antispoofing

Applications of Client Identity Information for Face Antispoofing

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