Face Authentication with Salient Local Features and Static Bayesian Network
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One of the major problem in face authentication systems is to deal with variations in illumination. In a \mbox{realistic} scenario, it is very likely that the lighting conditions of the probe image does not correspond to those of the gallery image, hence t ...
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 ...
In this paper, we propose a novel generative approach for face authentication, based on a Local Binary Pattern (LBP) description of the face. A generic face model is considered as a collection of LBP-histograms. Then, a client-specific model is obtained by ...
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 ...
In this paper, we propose a novel generative approach for face authentication, based on a Local Binary Pattern (LBP) description of the face. A generic face model is considered as a collection of LBP-histograms. Then, a client-specific model is obtained by ...
The objective of this thesis is to develop probabilistic graphical models for analyzing human interaction in meetings based on multimodel cues. We use meeting as a study case of human interactions since research shows that high complexity information is mo ...
The objective of this thesis is to develop probabilistic graphical models for analyzing human interaction in meetings based on multimodel cues. We use meeting as a study case of human interactions since research shows that high complexity information is mo ...
This thesis explores latent-variable probabilistic models for the analysis and classification of electroenchephalographic (EEG) signals used in Brain Computer Interface (BCI) systems. The first part of the thesis focuses on the use of probabilistic methods ...
The objective of this thesis is to develop probabilistic graphical models for analyzing human interaction in meetings based on multimodel cues. We use meeting as a study case of human interactions since research shows that high complexity information is mo ...
This thesis explores latent-variable probabilistic models for the analysis and classification of electroenchephalographic (EEG) signals used in Brain Computer Interface (BCI) systems. The first part of the thesis focuses on the use of probabilistic methods ...