Publication

Statistical Transformation Techniques for Face Verification Using Faces Rotated in Depth

Publications associées (45)

Graph Chatbot

Chattez avec Graph Search

Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.

AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.

Connectez-vous pour utiliser Chat avec Graph Search

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 / Robustness / Complexity Trade-Offs in Face Verification

Samy Bengio

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 ...

IDIAP2004

A probabilistic model of face mapping applied to person recognition

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 ...

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

On performance evaluation of face detection and localization algorithms

Jean-Philippe Thiran, Vlad Popovici

International Society for Magnetic Resonance in Medicine2004

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

New support vector algorithms for multicategorical data applied to real-time object recognition

Silvio Borer

Humans have the ability to learn. Having seen an object we can recognise it later. We can do this because our nervous system uses an efficient and robust visual processing and capabilities to learn from sensory input. On the other hand, designing algorithm ...

EPFL2003

A Symmetric Transformation for LDA-based Face Verification

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

Improving Face Verification using Symmetric Transformation

Sébastien Marcel

IDIAP2003

On Performance Evaluation of Face Detection and Localization Algorithms

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

IDIAP2003