Publications by Sébastien Marcel

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This paper presents an evaluation of verification and calibration performance of a face recognition system based on inter-session variability modeling. As an extension to the calibration through linear transformation of scores, categorical calibration is i ...

Any biometric recognizer is vulnerable to spoofing attacks and hence voice biometric, also called automatic speaker verification (ASV), is no exception; replay, synthesis, and conversion attacks all provoke false acceptances unless countermeasures are used ...

Due to its convenience, biometric authentication, especial face authentication, has become increasingly mainstream and thus is now a prime target for attackers. Presentation attacks and face morphing are typical types of attack. Previous research has shown ...

This paper addresses the problem of face presentation attack detection using different image modalities. In particular, the usage of short wave infrared (SWIR) imaging is considered. Face presentation attack detection is performed using recent models based ...

Homomorphic Encryption (HE) has become a wellknown tool for privacy-preserving recognition in biometric systems. Despite some important advantages of HE (such as preservation of recognition accuracy), there are two main drawbacks in the application of HE t ...

In this paper, we investigate the use of brain activity for person authentication. It has been shown in previous studies that the brain-wave pattern of every individual is unique and that the electroencephalogram (EEG) can be used for biometric identificat ...

This paper applies score and feature normalization techniques to parts-based Gaussian mixture model (GMM) face authentication. In particular, we propose to utilize techniques that are well established in state-of-the-art speaker authentication, and apply t ...

Face recognition has become a popular authentication tool in recent years. Modern state-of-the-art (SOTA) face recognition methods rely on deep neural networks, which extract discriminative features from face images. Although these methods have high recogn ...

In this paper we present a scalable and exact solution for probabilistic linear discriminant analysis (PLDA). PLDA is a probabilistic model that has been shown to provide state-of-the-art performance for both face and speaker recognition. However, it has o ...

Face recognition has evolved as a widely used biometric modality. However, its vulnerability against presentation attacks poses a significant security threat. Though presentation attack detection (PAD) methods try to address this issue, they often fail in ...

Morphing attacks are a threat to biometric systems where the biometric reference in an identity document can be altered. This form of attack presents an important issue in applications relying on identity documents such as border security or access control ...

In this work, we present a simple biometric indexing scheme which is binning and retrieving cancelable deep face templates based on frequent binary patterns. The simplicity of the proposed approach makes it applicable to unprotected as well as protected, i ...

Morphing attacks is a threat to biometric systems where the biometric reference in an identity document can be altered. This form of attack presents an important issue in applications relying on identity documents such as border security or access control. ...

In this paper, a novel statistical generative model to describe a face is presented, and is applied to the face authentication task. Classical generative models used so far in face recognition, such as Gaussian Mixture Models (GMMs) and Hidden Markov Model ...

This paper presents a survey on the recent use of Local Binary Patterns (LBPs) for face recognition. LBP is becoming a popular technique for face representation. It is a non-parametric kernel which summarizes the local spacial structure of an image and it ...

Identity spoofing is a contender for high-security face recognition applications. With the advent of social media and globalized search, our face images and videos are wide-spread on the internet and can be potentially used to attack biometric systems with ...

The location of the eyes is the most commonly used features to perform face normalization (i.e., alignment of facial features), which is an essential preprocessing stage of many face recognition systems. In this paper, we study the sensitivity of open sour ...

Backdoor attacks allow an attacker to embed functionality jeopardizing proper behavior of any algorithm, machine learning or not. This hidden functionality can remain inactive for normal use of the algorithm until activated by the attacker. Given how steal ...

While more accurate and reliable than ever, the trustworthiness of biometric verification systems is compromised by the emergence of spoofing attacks. Responding to this threat, numerous research publications address isolated spoofing detection, resulting ...

In this paper, we use a hill-climbing attack algorithm based on Bayesian adaption to test the vulnerability of two face recognition systems to indirect attacks. The attacking technique uses the scores provided by the matcher to adapt a global distribution ...

Sébastien Marcel

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Score Calibration in Face Recognition

Joint Speaker Verification and Anti-Spoofing in the i-Vector Space

Generating Master Faces for Use in PerformingWolf Attacks on Face Recognition Systems

Deep Models and Shortwave Infrared Information to Detect Face Presentation Attacks

Hybrid Protection of Biometric Templates by Combining Homomorphic Encryption and Cancelable Biometrics

Person Authentication using Brainwaves (EEG) and Maximum A Posteriori Model Adaptation

Cross-pollination of normalisation techniques from speaker to face authentication using Gaussian mixture models

On the Recognition Performance of BioHashing on state-of-the-art Face Recognition models

A Scalable Formulation of Probabilistic Linear Discriminant Analysis: Applied to Face Recognition

Learning One Class Representations for Face Presentation Attack Detection using Multi-channel Convolutional Neural Networks

Are GAN-based Morphs Threatening Face Recognition?

Indexing Protected Deep Face Templates by Frequent Binary Patterns

Vulnerability Analysis of Face Morphing Attacks from Landmarks and Generative Adversarial Networks

A novel statistical generative model dedicated to face recognition

On the Recent Use of Local Binary Patterns for Face Authentication

Motion-Based Counter-Measures to Photo Attacks in Face Recognition

Impact of Eye Detection Error on Face Recognition Performance

An anomaly detection approach for backdoored neural networks: face recognition as a case study

Biometrics Evaluation Under Spoofing Attacks

On the vulnerability of face verification systems to hill-climbing attacks