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
An efficient face detection algorithm which can detect multiple faces in a cluttered en-vironment is...
We present an algorithm for shape detection and apply it to frontal views of faces in still grey lev...
While much is known about how faces are recognized, little is known about how a face is first detect...
An algorithm for locating quasi-frontal views of human faces in cluttered scenes is presented. The a...
An important topic in face recognition as well as in video coding or multi-modal human machine inter...
In this paper, a face localization system is proposed in which local detectors are coupled with a st...
In this paper we present a way to regard the combined face detection and facial feature extraction p...
. We present a distribution-based modeling scheme for representing and detecting human faces in clut...
In this paper, we consider the problem of robust localization of faces and some of their facial feat...
In this work, I focus in a simple parameter-free statistical model that requires few training data a...
In this paper, we consider the problem of robust localization of faces and some of their facial feat...
Automatic face detection in digital video is becoming a very important research topic, due to its wi...
This paper presents a new face parts information analyzer, as a promising model for detecting faces ...
Many current human face detection algorithms make implicit assumptions about the scale, orientation ...
The unconstrained acquisition of facial data in real-world conditions may result in face images with...
An efficient face detection algorithm which can detect multiple faces in a cluttered en-vironment is...
We present an algorithm for shape detection and apply it to frontal views of faces in still grey lev...
While much is known about how faces are recognized, little is known about how a face is first detect...
An algorithm for locating quasi-frontal views of human faces in cluttered scenes is presented. The a...
An important topic in face recognition as well as in video coding or multi-modal human machine inter...
In this paper, a face localization system is proposed in which local detectors are coupled with a st...
In this paper we present a way to regard the combined face detection and facial feature extraction p...
. We present a distribution-based modeling scheme for representing and detecting human faces in clut...
In this paper, we consider the problem of robust localization of faces and some of their facial feat...
In this work, I focus in a simple parameter-free statistical model that requires few training data a...
In this paper, we consider the problem of robust localization of faces and some of their facial feat...
Automatic face detection in digital video is becoming a very important research topic, due to its wi...
This paper presents a new face parts information analyzer, as a promising model for detecting faces ...
Many current human face detection algorithms make implicit assumptions about the scale, orientation ...
The unconstrained acquisition of facial data in real-world conditions may result in face images with...
An efficient face detection algorithm which can detect multiple faces in a cluttered en-vironment is...
We present an algorithm for shape detection and apply it to frontal views of faces in still grey lev...
While much is known about how faces are recognized, little is known about how a face is first detect...