Sébastien Marcel

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Publications associées (51)

Detection of Age-Induced Makeup Attacks on Face Recognition Systems Using Multi-Layer Deep Features

Sébastien Marcel, Zohreh Mostaani

Makeup is a simple and easy instrument that can alter the appearance of a person’s face, and hence, create a presentation attack on face recognition (FR) systems. These attacks, especially the ones mimicking ageing, are difficult to detect due to their clo ...

2020

Low-latency speaker spotting with online diarization and detection

Sébastien Marcel, Nicholas Evans

This paper introduces a new task termed low-latency speaker spotting (LLSS). Related to security and intelligence applications, the task involves the detection, as soon as possible, of known speakers within multi-speaker audio streams. The paper describes ...

2018

Towards directly modeling raw speech signal for speaker verification using CNNs

Sébastien Marcel, Hannah Muckenhirn

Speaker verification systems traditionally extract and model cepstral features or filter bank energies from the speech signal. In this paper, inspired by the success of neural network-based approaches to model directly raw speech signal for applications su ...

IEEE2018

Biometrics: In Search of Identity and Security (Q & A)

Sébastien Marcel

To address the issues like identity theft and security threats, a continuously evolving technology known as biometrics is presently being deployed in a wide range of personal, government, and commercial applications. Despite the great progress in the field ...

2018

On Learning Vocal Tract System Related Speaker Discriminative Information from Raw Signal Using CNNs

Sébastien Marcel, Hannah Muckenhirn

In a recent work, we have shown that speaker verification systems can be built where both features and classifiers are directly learned from the raw speech signal with convolutional neural networks (CNNs). In this framework, the training phase also decides ...

ISCA-INT SPEECH COMMUNICATION ASSOC2018

Impact of score fusion on voice biometrics and presentation attack detection in cross-database evaluations

Sébastien Marcel

Research in the area of automatic speaker verification (ASV) has been advanced enough for the industry to start using ASV systems in practical applications. However, these systems are highly vulnerable to spoofing or presentation attacks, limiting their wi ...

2017

Long-Term Spectral Statistics for Voice Presentation Attack Detection

Mathew Magimai Doss, Sébastien Marcel, Hannah Muckenhirn

Automatic speaker verification systems can be spoofed through recorded, synthetic or voice converted speech of target speakers. To make these systems practically viable, the detection of such attacks, referred to as presentation attacks, is of paramount in ...

2017

A reproducible study on remote heart rate measurement

Sébastien Marcel, André Anjos, Guillaume Heusch

This paper studies the problem of reproducible research in remote photoplethysmography (rPPG). Most of the work published in this domain is assessed on privately-owned databases, making it difficult to evaluate proposed algorithms in a standard and princip ...

2017

Deeply Vulnerable -- a study of the robustness of face recognition to presentation attacks

Sébastien Marcel, Amir Mohammadi

The vulnerability of deep-learning-based face-recognition (FR) methods, to presentation attacks (PA), is studied in this study. Recently, proposed FR methods based on deep neural networks (DNN) have been shown to outperform most other methods by a signific ...

Inst Engineering Technology-Iet2017

Keystroke Biometrics Ongoing Competition

Sébastien Marcel, André Anjos

This paper presents the first Keystroke Biometrics Ongoing Competition (KBOC) organized to establish a reproducible baseline in person authentication using keystroke biometrics. The competition has been developed using the BEAT platform and includes one of ...

2016

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