Vulnerability Analysis of Face Morphing Attacks from Landmarks and Generative Adversarial Networks
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The principal objective of this thesis is to investigate approaches toward a robust automatic face authentication (AFA) system in weakly constrained environments. In this context, we develop new algorithms based on local features and generative models. In ...
This volume constitutes the post-conference proceedings of the First European Workshop on Biometrics and Identity Management, BIOID 2008, held in Roskilde, Denmark, during May 7-9, 2008. The 23 regular papers presented were carefully selected from numerous ...
In this paper, a novel statistical generative model to describe a face is presented, and is applied on the face authentication task. Classical generative models used so far in face recognition, such as Gaussian Mixture Models (GMM) and Hidden Markov Models ...
OPPORTUNITY is project under the EU FET-Open funding1 in which we develop mobile systems to recognize human activity in dynamically varying sensor setups. The system autonomously discovers available sensors around the user and self-configures to recognize ...
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 ...
In this thesis, we address the problem of face modelling by using dedicated statistical generative models, with an application to the face authentication task. Face authentication consists in either accepting or rejecting a user's claim supported by its fa ...
In this paper, the problem of face authentication using salient facial features together with statistical generative models is adressed. Actually, classical generative models, and Gaussian Mixture Models in particular make strong assumptions on the way obs ...
In this paper, the problem of face authentication using salient facial features together with statistical generative models is adressed. Actually, classical generative models, and Gaussian Mixture Models in particular make strong assumptions on the way obs ...