The Effectiveness of Depth Data in Liveness Face Authentication Using 3D Sensor Cameras

Albakri, Ghazel; Alghowinem, Sharifa

doi:10.3390/s19081928

Cited by 19 publications

(6 citation statements)

References 45 publications

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“…In [19] a study was presented to assess the liveness detection of 3D cameras. The authors presented a system that utilized Kinect sensor for testing and comparing the effectiveness of depth data in spoof detection.…”

Section: Multiple Sensorsmentioning

confidence: 99%

A Contemporary Survey of Multimodal Presentation Attack Detection Techniques: Challenges and Opportunities

2021

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Biometric recognition is a broad and dynamic field of research but the main problem of this field is spoofing attack or presentation attack "use of fake biometric in place of the real biometric sample from original user". Liveness detection is the prime countermeasure to spoofing attacks, which is based on the principle that some additional information can be obtained to verify that the produced data is genuine or not by a standard verification system. It utilized anatomical signs of life, such as facial expression, blinking of eyes, movement of the head, etc. This paper presents a comprehensive review of various liveness detection techniques based on a multimodal biometric system, in which physiological and behavioral properties are used to differentiate between genuine and fake biometric traits. Multimodal systems utilize two or more biometric traits which makes them more secure as compared to unimodal systems. These systems overcome the limitations of the unimodal system such as spoof attack, noisy data, non-universality, distinctiveness, and intra-class variations, etc. Hence to make the biometric systems more secure and robust, multimodal techniques are used. In this paper, we categorized and discuss the various multimodal biometric techniques proposed by various researchers in the last decade, and a new classification is also developed for the same. This paper covers theories, methodology, evaluation datasets, and aims at future work in this field of research.

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Section: Multiple Sensorsmentioning

confidence: 99%

A Contemporary Survey of Multimodal Presentation Attack Detection Techniques: Challenges and Opportunities

2021

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“…Indeed, some other methods as liveness detection must be added to obtain a reliable face recognition technique. Furthermore, the technological improvement has made 3D data usage promising since depth map details are more and more refined and robust to spoofing attacks [2].…”

Section: Face Identificationmentioning

confidence: 99%

Analysis of RGB-D camera technologies for supporting different facial usage scenarios

Ulrich

Vezzetti

Moos

et al. 2020

Multimed Tools Appl

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Recently a wide variety of applications has been developed integrating 3D functionalities. Advantages given by the possibility of relying on depth information allows the developers to design new algorithms and to improve the existing ones. In particular, for what concerns face morphology, 3D has led to the possibility to obtain face depth maps highly close to reality and consequently an improvement of the starting point for further analysis such as Face Detection, Face Authentication, Face Identification and Face Expression Recognition. The development of the aforementioned applications would have been impossible without the progress of sensor technologies for obtaining 3D information. Several solutions have been adopted over time. In this paper, emphasis is put on passive stereoscopy, structured light, time-of-flight (ToF) and active stereoscopy, namely the most used technologies for the cameras design and fulfilment according to the literature. The aim of this article is to investigate facial applications and to examine 3D camera technologies to suggest some guidelines for addressing the correct choice of a 3D sensor according to the application that has to be developed.

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“…Albakri and Alghowinem [ 28 ] evaluated the liveness detection to suggest solutions that account for the weaknesses found in detecting spoofing attacks. They performed a proof-of-concept study to assess the liveness detection of 3D cameras in three devices, where the outcomes suggest that having more flexibility resulted in achieving a higher rate in detecting spoofing attacks.…”

Section: Related Workmentioning

confidence: 99%

Convolutional Neural Network Approach for Multispectral Facial Presentation Attack Detection in Automated Border Control Systems

Sánchez‐Sánchez

Conde

Gómez-Ayllón

et al. 2020

Entropy

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Automated border control systems are the first critical infrastructure point when crossing a border country. Crossing border lines for unauthorized passengers is a high security risk to any country. This paper presents a multispectral analysis of presentation attack detection for facial biometrics using the learned features from a convolutional neural network. Three sensors are considered to design and develop a new database that is composed of visible (VIS), near-infrared (NIR), and thermal images. Most studies are based on laboratory or ideal conditions-controlled environments. However, in a real scenario, a subject’s situation is completely modified due to diverse physiological conditions, such as stress, temperature changes, sweating, and increased blood pressure. For this reason, the added value of this study is that this database was acquired in situ. The attacks considered were printed, masked, and displayed images. In addition, five classifiers were used to detect the presentation attack. Note that thermal sensors provide better performance than other solutions. The results present better outputs when all sensors are used together, regardless of whether classifier or feature-level fusion is considered. Finally, classifiers such as KNN or SVM show high performance and low computational level.

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The Effectiveness of Depth Data in Liveness Face Authentication Using 3D Sensor Cameras

Cited by 19 publications

References 45 publications

A Contemporary Survey of Multimodal Presentation Attack Detection Techniques: Challenges and Opportunities

A Contemporary Survey of Multimodal Presentation Attack Detection Techniques: Challenges and Opportunities

Analysis of RGB-D camera technologies for supporting different facial usage scenarios

Convolutional Neural Network Approach for Multispectral Facial Presentation Attack Detection in Automated Border Control Systems

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