Face authentication based on local features and generative models
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Statistical pattern recognition occupies a central place in the general context of machine learning techniques, as it provides the theoretical insights and the practical means for solving a variety of problems ranging from character recognition to face rec ...
Within the field of pattern recognition, biometrics is the discipline which is concerned with the automatic recognition of a person based on his/her physiological or behavioral characteristics. Face recognition, a central area in biometrics, is a very chal ...
In much of the literature devoted to face recognition, experiments are performed with controlled images (e.g. manual face localization, controlled lighting, background and pose); however, a practical recognition system has to be robust to more challenging ...
Face localization is the process of finding the exact position of a face in a given image. This can be useful in several applications such as face tracking or person authentication. The purpose of this paper is to show that the error made during the locali ...
Face localization is the process of finding the exact position of a face in a given image. This can be useful in several applications such as face tracking or person authentication. The purpose of this paper is to show that the error made during the locali ...
This paper establishes tight bounds on the best-case time-complexity of distributed atomic read/write storage implementations that tolerate worst-case conditions. We study asynchronous robust implementations where a writer and a set of reader processes (cl ...
Combining multiple information sources, typically from several data streams is a very promising approach, both in experiments and to some extents in various real-life applications. A system that uses more than one behavioural and physiological characterist ...
This study investigates a new client-dependent normalisation to improve biometric authentication systems. There exists many client-de-pendent score normalisation techniques applied to speaker authentication, such as Z-Norm, D-Norm and T-Norm. Such normalis ...
The performance of face authentication systems has steadily improved over the last few years. State-of-the-art methods use the projection of the gray-scale face image into a Linear Discriminant subspace as input of a classifier such as Support Vector Machi ...
It has been previously demonstrated that systems based on local features and relatively complex statistical models, namely 1D Hidden Markov Models (HMMs) and pseudo-2D HMMs, are suitable for face recognition. Recently, a simpler statistical model, namely t ...
