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Boosting Pixel-based Classifiers for Face Verification

Publications associées (88)

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A Real-Time Deformable Detector

Pascal Fua, François Fleuret, Karim Ali, David Hasler

We propose a new learning strategy for object detection. The proposed scheme forgoes the need to train a collection of detectors dedicated to homogeneous families of poses, and instead learns a single classifier that has the inherent ability to deform base ...

Institute of Electrical and Electronics Engineers2012

Selection and Combination of Local Gabor Classiﬁers for Robust Face Veriﬁcation

Hazim Kemal Ekenel, Nuri Murat Arar, Hua Gao

Gabor features have been extensively used for facial image analysis due to their powerful representation capabilities. This paper focuses on selecting and combining multiple Gabor classiﬁers that are trained on, for example, different scales and local regi ...

2012

Face Detection using Ferns

Sébastien Marcel, Venkatesh Bala Subburaman

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 ...

Idiap2011

Inter-session Variability Modelling and Joint Factor Analysis for Face Authentication

Sébastien Marcel

This paper applies inter-session variability modelling and joint factor analysis to face authentication using Gaussian Mixture Models. These techniques, originally developed for speaker authentication, aim to explicitly model and remove detrimental within- ...

Idiap2011

Learning Pose Invariant and Covariant Classifiers from Image Sequences

Mustafa Özuysal

Object tracking and detection over a wide range of viewpoints is a long-standing problem in Computer Vision. Despite significant advance in wide-baseline sparse interest point matching and development of robust dense feature models, it remains a largely op ...

EPFL2010

Fast Bounding Box Estimation based Face Detection

Sébastien Marcel, Venkatesh Bala Subburaman

The sliding window approach is the most widely used technique to detect an object from an image. In the past few years, classifiers have been improved in many ways to increase the scanning speed. Apart from the classifier design (such as cascade), the scan ...

2010

Fast Bounding Box Estimation based Face Detection

Sébastien Marcel, Venkatesh Bala Subburaman

Idiap2010

An Alternative Scanning Strategy to Detect Faces

Sébastien Marcel, Venkatesh Bala Subburaman

The sliding window approach is the most widely used technique to detect faces in an image. Usually a classifier is applied on a regular grid and to speed up the scanning, the grid spacing is increased, which increases the number of miss detections. In this ...

2010

Fast Keypoint Recognition using Random Ferns

Pascal Fua, Vincent Lepetit, Michael Calonder, Mustafa Özuysal

While feature point recognition is a key component of modern approaches to object detection, existing approaches require computationally expensive patch preprocessing to handle perspective distortion. In this paper, we show that formulating the problem in ...

2010

Mobile Biometry (MOBIO) Face and Speaker Verification Evaluation

Sébastien Marcel

This paper evaluates the performance of face and speaker verification techniques in the context of a mobile environment. The mobile environment was chosen as it provides a realistic and challenging test-bed for biometric person verification techniques to o ...

Idiap2010