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Boosting Pixel-based Classifiers for Face Verification

Publications associées (55)

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Face Detection using SVM Trained in Eigenfaces Space

Jean-Philippe Thiran, Vlad Popovici

The central problem in the case of face detectors is to build a face class model. We present a method for face class modeling in the eigenfaces space using a large-margin classifier like SVM. Two main issues are addressed: what is the required number of ei ...

SPIE2003

Real-Time Face Detection Using Boosting Learning in Hierarchical Feature Spaces

Daniel Gatica-Perez, Dong Zhang

Boosting-based methods have recently led to the state-of-the-art face detection systems. In these systems, weak classifiers to be boosted are based on simple, local, Haar-like features. However, it can be empirically observed that in later stages of the bo ...

IDIAP2003

Independent Component Analysis and Support Vector Machine for Face Feature Extraction

Jean-Philippe Thiran, Gianluca Antonini, Vlad Popovici

We propose Independent Component Analysis representation and Support Vector Machine classification to extract facial features in a face detection/localization context. The goal is to find a better space where project the data in order to build ten differen ...

IEEE2003

Improving Face Verification using Symmetric Transformation

Sébastien Marcel

One of the major problem in face verification is to deal with a few number of images per person to train the system. A solution to that problem is to generate virtual samples from an unique image by doing simple geometric transformations such as translatio ...

IDIAP2003

A Symmetric Transformation for LDA-based Face Verification

Sébastien Marcel

IDIAP2003

Face Verification Using Synthesized Non-Frontal Models

Samy Bengio

{NOTE}: {THIS} {REPORT} {HAS} {BEEN} {SUPERSEDED} {BY} {IDIAP-RR} 04-04. {I}n this report we address the problem of non-frontal face verification when only a frontal training image is available (e.g. a passport photograph) by augmenting a client's frontal ...

IDIAP2003

Face Class Modeling in Eigenfaces Space

Jean-Philippe Thiran, Vlad Popovici

We present a method for face class modeling in the eigenfaces space using a large-margin classifier like SVM. Another issue addressed is how to select the number of eigenfaces to achieve a good classification rate. As the experimental evidence show, genera ...

SPIE2003

A State-of-the-art Neural Network for Robust Face Verification

Sébastien Marcel, Samy Bengio

The performance of face verification systems has steadily improved over the last few years, mainly focusing on models rather than on feature processing. State-of-the-art methods often use the gray-scale face image as input. In this paper, we propose to use ...

IDIAP2002

Mixture Models for Unsupervised and Supervised Learning

In a society which produces and consumes an ever increasing amount of information, methods which can make sense out of all this data become of crucial importance. Machine learning tries to develop models which can make the information load accessible. Thre ...

IDIAP2000

Mixture Models for Unsupervised and Supervised Learning

École Polytechnique Fédérale de Lausanne, Computer Science Department2000