User Authentication via Adapted Statistical Models of Face Images
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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 report, we propose a statistical model to deal with the discrete-distribution data varying over time. The proposed model -- HMM+DM -- extends the Dirichlet mixture model to the dynamic case: Hidden Markov Model with Dirichlet mixture output. Both t ...
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 ...
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 ...
Models dealing directly with the raw acoustic speech signal are an alternative to conventional feature-based HMMs. A popular way to model the raw speech signal is by means of an autoregressive (AR) process. Being too simple to cope with the nonlinearity of ...
The purpose of Face localization is to determine the coordinates of a face in a given image. It is a fundamental research area in computer vision because it serves, as a necessary first step, any face processing systems, such as automatic face recognition, ...
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 ...
Feature extraction based on different types of signal filters has received a lot of attention in the context of face recognition. It generally results into extremely high dimensional feature vectors, and sampling of the coefficients is required to reduce t ...
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 ...
We address the need for robust detection of obstructed human features in complex environments, with a focus on intelligent surgical UIs. In our setup, real-time detection is used to find features without the help of local (spatial or temporal) information. ...