Add to ORKGAn algorithm for locating quasi-frontal views of human faces in cluttered scenes is presented. The algorithm works by coupling a set of local feature detectors with a statistical model of the mutual distances between facial features it is invariant with respect to translation, rotation (in the plane), and scale and can handle partial occlusions of the face. On a challenging database with complicated and varied backgrounds, the algorithm achieved a correct localization rate of 95% in images where the face appeared quasi-frontally
International audienceIn this paper we present a face model based on learning a relation between loc...
Human face detection has always been an important problem for face, expression and gesture recogniti...
The unconstrained acquisition of facial data in real-world conditions may result in face images with...
An algorithm for locating quasi-frontal views of human faces in cluttered scenes is presented. The a...
In this paper, a face localization system is proposed in which local detectors are coupled with a st...
Abstract — A novel face recognition method is proposed, in which face images are represented by a se...
We present an example-based learning approach for locating vertical frontal views of human faces i...
In this paper, we consider the problem of robust localization of faces and some of their facial feat...
This thesis considers the problem of recognizing human faces despite variations in illumination, pos...
Localizing facial landmarks is a fundamental step in fa-cial image analysis. However, the problem is...
In this paper, we consider the problem of robust localization of faces and some of their facial feat...
An important topic in face recognition as well as in video coding or multi-modal human machine inter...
. We present a distribution-based modeling scheme for representing and detecting human faces in clut...
In this work, I focus in a simple parameter-free statistical model that requires few training data a...
The presence of occlusions in facial images is inevitable in unconstrained scenarios. However recogn...
International audienceIn this paper we present a face model based on learning a relation between loc...
Human face detection has always been an important problem for face, expression and gesture recogniti...
The unconstrained acquisition of facial data in real-world conditions may result in face images with...
An algorithm for locating quasi-frontal views of human faces in cluttered scenes is presented. The a...
In this paper, a face localization system is proposed in which local detectors are coupled with a st...
Abstract — A novel face recognition method is proposed, in which face images are represented by a se...
We present an example-based learning approach for locating vertical frontal views of human faces i...
In this paper, we consider the problem of robust localization of faces and some of their facial feat...
This thesis considers the problem of recognizing human faces despite variations in illumination, pos...
Localizing facial landmarks is a fundamental step in fa-cial image analysis. However, the problem is...
In this paper, we consider the problem of robust localization of faces and some of their facial feat...
An important topic in face recognition as well as in video coding or multi-modal human machine inter...
. We present a distribution-based modeling scheme for representing and detecting human faces in clut...
In this work, I focus in a simple parameter-free statistical model that requires few training data a...
The presence of occlusions in facial images is inevitable in unconstrained scenarios. However recogn...
International audienceIn this paper we present a face model based on learning a relation between loc...
Human face detection has always been an important problem for face, expression and gesture recogniti...
The unconstrained acquisition of facial data in real-world conditions may result in face images with...