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Vlad Popovici

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Publications associées (28)

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Extraction of Audio Features Specific to Speech using Information Theory and Differential Evolution

Jean-Philippe Thiran, Jean-Marc Vesin, Murat Kunt, Vlad Popovici, Patricia Besson

We present a method that exploits an information theoretic framework to extract optimized audio features using the video information. A simple measure of mutual information (MI) between the resulting audio features and the video ones allows to detect the a ...

2005

Face Detection with Mixtures of Boosted Discriminant Features

Jean-Philippe Thiran, Vlad Popovici, Julien Meynet

Detecting faces in images is a key step in numerous computer vision applications as face recognition for example. Face detection is a difficult task in image analysis because of the large face intra-class variability which is due to the important influence ...

2005

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We present a method for combining a number of Support Vector Machines trained independently in the eigenface space and we apply it to face class modeling. We first train several ...

IEEE2005

Kernel Matching Pursuit for Large Datasets

Jean-Philippe Thiran, Vlad Popovici

Kernel matching pursuit is a greedy algorithm for building an approximation of a discriminant function as a linear combination of some basis functions selected from a kernel-induced dictionary. Here we propose a modification of the kernel matching pursuit ...

2005

Kernel-based classifiers with applications to face detection

Vlad Popovici

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 ...

EPFL2004

On Performance Evaluation of Face Detection and Localization Algorithms

Jean-Philippe Thiran, Sébastien Marcel, Vlad Popovici, Yann Rodriguez

When comparing different methods for face detection or localization, one realizes that just simply comparing the reported results is misleading as, even if the results are reported on the same dataset, different authors have different views of what a corre ...

2004

Pattern Recognition using Higher-Order Local Autocorrelation Coefficients

Jean-Philippe Thiran, Vlad Popovici

The autocorrelations have been previously used as features for 1D or 2D signal classification in a wide range of applications, like texture classification, face detection and recognition, EEG signal classification, and so on. However, in almost all the cas ...

2004

Face Class Modeling Using Mixture of SVMs

Jean-Philippe Thiran, Vlad Popovici, Julien Meynet

We present a method for face detection which uses a new SVM structure trained in an expert manner in the eigenface space. This robust method has been introduced as a post processing step in a realtime face detection system. The principle is to train severa ...

EPFL2004

International Society for Magnetic Resonance in Medicine2004

A sparse classifier is guaranteed to generalize better than a denser one, given they perform identical on the training set. However, methods like Support Vector Machine, even if they produce relatively sparse models, are known to scale linearly as the numb ...

IEEE2004