Face Detection with Mixtures of Boosted Discriminant Features
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This paper discusses the use of ferns (a set of binary features) for face detection. The binary feature used here is the sign of pixel intensity difference. Ferns were first introduced for keypoint recognition and showed good performance, and improving the ...
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 dec ...
Face verification in the simultaneous presence of age progression and changing face-image quality is an important problem that has not been widely addressed. In this paper, we study the problem by designing and evaluating a generalized Q-stack model, which ...
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The search for robust features for face recognition in uncontrolled environments is an important topic of research. In particular, there is a high interest in Gabor-based features which have invariance properties to simple geometrical transformations. In t ...
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, 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 ...
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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 ...