Results 1 - 10 of 510,779

Face Recognition: A Literature Survey

by W. Zhao, R. Chellappa, P. J. Phillips, A. Rosenfeld , 2000
"... ... This paper provides an up-to-date critical survey of still- and video-based face recognition research. There are two underlying motivations for us to write this survey paper: the first is to provide an up-to-date review of the existing literature, and the second is to offer some insights into ..."
Abstract - Cited by 1363 (21 self) - Add to MetaCart
... This paper provides an up-to-date critical survey of still- and video-based face recognition research. There are two underlying motivations for us to write this survey paper: the first is to provide an up-to-date review of the existing literature, and the second is to offer some insights

Face recognition: features versus templates

by Roberto Brunelli, Tomaso Poggio - IEEE Transactions on Pattern Analysis and Machine Intelligence , 1993
"... Abstract-Over the last 20 years, several different techniques have been proposed for computer recognition of human faces. The purpose of this paper is to compare two simple but general strategies on a common database (frontal images of faces of 47 people: 26 males and 21 females, four images per per ..."
Abstract - Cited by 737 (25 self) - Add to MetaCart
Abstract-Over the last 20 years, several different techniques have been proposed for computer recognition of human faces. The purpose of this paper is to compare two simple but general strategies on a common database (frontal images of faces of 47 people: 26 males and 21 females, four images per

Overview of the Face Recognition Grand Challenge

by P. Jonathon Phillips, Patrick J. Flynn, Todd Scruggs, Kevin W. Bowyer, Jin Chang, Kevin Hoffman, Joe Marques, Jaesik Min, William Worek - In IEEE CVPR , 2005
"... Over the last couple of years, face recognition researchers have been developing new techniques. These developments are being fueled by advances in computer vision techniques, computer design, sensor design, and interest in fielding face recognition systems. Such advances hold the promise of reducin ..."
Abstract - Cited by 446 (32 self) - Add to MetaCart
Over the last couple of years, face recognition researchers have been developing new techniques. These developments are being fueled by advances in computer vision techniques, computer design, sensor design, and interest in fielding face recognition systems. Such advances hold the promise

Face recognition using laplacianfaces

by Xiaofei He, Shuicheng Yan, Yuxiao Hu, Partha Niyogi, Hong-jiang Zhang - IEEE Transactions on Pattern Analysis and Machine Intelligence , 2005
"... Abstract—We propose an appearance-based face recognition method called the Laplacianface approach. By using Locality Preserving Projections (LPP), the face images are mapped into a face subspace for analysis. Different from Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) wh ..."
Abstract - Cited by 381 (39 self) - Add to MetaCart
Abstract—We propose an appearance-based face recognition method called the Laplacianface approach. By using Locality Preserving Projections (LPP), the face images are mapped into a face subspace for analysis. Different from Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA

The FERET evaluation methodology for face recognition algorithms

by P. Jonathon Phillips, Hyeonjoon Moon, Syed A. Rizvi, Patrick J. Rauss - In (a) Example 1 (b) Example 1 (c) Right ear) (d) Mirroed Left ear
"... AbstractÐTwo of the most critical requirements in support of producing reliable face-recognition systems are a large database of facial images and a testing procedure to evaluate systems. The Face Recognition Technology (FERET) program has addressed both issues through the FERET database of facial i ..."
Abstract - Cited by 1096 (27 self) - Add to MetaCart
AbstractÐTwo of the most critical requirements in support of producing reliable face-recognition systems are a large database of facial images and a testing procedure to evaluate systems. The Face Recognition Technology (FERET) program has addressed both issues through the FERET database of facial

View-Based and Modular Eigenspaces for Face Recognition

by Alex Pentland, Baback Moghaddam, Thad Starner - IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION & PATTERN RECOGNITION , 1994
"... In this work we describe experiments with eigenfaces for recognition and interactive search in a large-scale face database. Accurate visual recognition is demonstrated using a database of o(10^3) faces. The problem of recognition under general viewing orientation is also explained. A view-based mul ..."
Abstract - Cited by 770 (15 self) - Add to MetaCart
In this work we describe experiments with eigenfaces for recognition and interactive search in a large-scale face database. Accurate visual recognition is demonstrated using a database of o(10^3) faces. The problem of recognition under general viewing orientation is also explained. A view

Robust face recognition via sparse representation

by John Wright, Allen Y. Yang, Arvind Ganesh, S. Shankar Sastry, Yi Ma - IEEE TRANS. PATTERN ANALYSIS AND MACHINE INTELLIGENCE , 2008
"... We consider the problem of automatically recognizing human faces from frontal views with varying expression and illumination, as well as occlusion and disguise. We cast the recognition problem as one of classifying among multiple linear regression models, and argue that new theory from sparse signa ..."
Abstract - Cited by 916 (41 self) - Add to MetaCart
We consider the problem of automatically recognizing human faces from frontal views with varying expression and illumination, as well as occlusion and disguise. We cast the recognition problem as one of classifying among multiple linear regression models, and argue that new theory from sparse

Face description with local binary patterns: Application to face recognition

by Abdenour Hadid, Senior Member - IEEE Trans. Pattern Analysis and Machine Intelligence , 2006
"... Abstract—This paper presents a novel and efficient facial image representation based on local binary pattern (LBP) texture features. The face image is divided into several regions from which the LBP feature distributions are extracted and concatenated into an enhanced feature vector to be used as a ..."
Abstract - Cited by 509 (27 self) - Add to MetaCart
face descriptor. The performance of the proposed method is assessed in the face recognition problem under different challenges. Other applications and several extensions are also discussed. Index Terms—Facial image representation, local binary pattern, component-based face recognition, texture features

Face Recognition Based on Fitting a 3D Morphable Model

by Volker Blanz, Thomas Vetter - IEEE Trans. Pattern Anal. Mach. Intell , 2003
"... Abstract—This paper presents a method for face recognition across variations in pose, ranging from frontal to profile views, and across a wide range of illuminations, including cast shadows and specular reflections. To account for these variations, the algorithm simulates the process of image format ..."
Abstract - Cited by 546 (19 self) - Add to MetaCart
Abstract—This paper presents a method for face recognition across variations in pose, ranging from frontal to profile views, and across a wide range of illuminations, including cast shadows and specular reflections. To account for these variations, the algorithm simulates the process of image

Face recognition by independent component analysis

by Marian Stewart Bartlett, Javier R. Movellan, Terrence J. Sejnowski - IEEE Transactions on Neural Networks , 2002
"... Abstract—A number of current face recognition algorithms use face representations found by unsupervised statistical methods. Typically these methods find a set of basis images and represent faces as a linear combination of those images. Principal component analysis (PCA) is a popular example of such ..."
Abstract - Cited by 333 (5 self) - Add to MetaCart
Abstract—A number of current face recognition algorithms use face representations found by unsupervised statistical methods. Typically these methods find a set of basis images and represent faces as a linear combination of those images. Principal component analysis (PCA) is a popular example
Results 1 - 10 of 510,779