Sébastien Marcel

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Publications associées (51)

Session variability modelling for face authentication

Sébastien Marcel, Laurent El Shafey

This study examines session variability modelling for face authentication using Gaussian mixture models. Session variability modelling aims to explicitly model and suppress detrimental within-class (inter-session) variation. The authors examine two techniq ...

2013

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

Sébastien Marcel, Laurent El Shafey

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 ...

Ieee Computer Soc2013

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

Sébastien Marcel

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 ...

2012

A Fast Parts-based Approach to Speaker Verification using Boosted Slice Classifiers

Mathew Magimai Doss, Sébastien Marcel, Anindya Roy

Speaker verification on portable devices like smartphones is gradually becoming popular. In this context, two issues need to be considered: 1) such devices have relatively limited computation resources, and 2) they are liable to be used everywhere, possibl ...

2012

Feature distribution modelling techniques for 3D face recognition

Sébastien Marcel

This paper shows that Hidden Markov Models (HMMs) can be effectively ap- plied to 3D face data. The examined HMM techniques are shown to be superior to a previously examined Gaussian Mixture Model (GMM) technique. Experi- ments conducted on the Face Recogn ...

2010

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

Sébastien Marcel

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 ...

2010

A novel statistical generative model dedicated to face recognition

Guillaume Heusch, Sébastien Marcel

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 ...

2010

A comparative study of two state-of-the-art sequence processing techniques for hand gesture recognition

Sébastien Marcel, Agnès Just

In this paper, we address the problem of the recognition of isolated, complex, dynamic hand gestures. The goal of this paper is to provide an empirical comparison of two state-of-the-art techniques for temporal event modeling combined with specific feature ...

2009

Parts-Based Face Verification using Local Frequency Bands

Sébastien Marcel

In this paper we extend the Parts-Based approach of face veriﬁcation by performing a frequency-based decomposition. The Parts-Based approach divides the face into a set of blocks which are then considered to be separate observations, this is a spatial deco ...

Springer2009

On the Recent Use of Local Binary Patterns for Face Authentication

Yann Rodriguez, Guillaume Heusch, Sébastien Marcel

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 ...

2007

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

Sébastien Marcel, José del Rocio Millán Ruiz

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 ...

2007

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