Journal ArticleDOI
The FERET evaluation methodology for face-recognition algorithms
TLDR
Two 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.Abstract:
Two 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 images and the establishment of the FERET tests. To date, 14,126 images from 1,199 individuals are included in the FERET database, which is divided into development and sequestered portions of the database. In September 1996, the FERET program administered the third in a series of FERET face-recognition tests. The primary objectives of the third test were to 1) assess the state of the art, 2) identify future areas of research, and 3) measure algorithm performance.read more
Citations
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Journal ArticleDOI
Back projection: An effective postprocessing method for GAN-based face sketch synthesis
TL;DR: The proposed back projection strategy can be extended to other GAN-based image-to-image translation problems and is inspired by the recent success in generating images of generative adversarial networks (GAN).
Journal ArticleDOI
Toward Realistic Face Photo–Sketch Synthesis via Composition-Aided GANs
TL;DR: Zhang et al. as discussed by the authors proposed a novel composition-aided generative adversarial network (CA-GAN) for face photo-sketch synthesis, which utilizes paired inputs, including a face photo/Sketch and the corresponding pixelwise face labels for generating a sketch/photo.
Book ChapterDOI
Recognising persons by their iris patterns
TL;DR: The iris recognition algorithms are explained, results of 9.1 million comparisons among eye images from trials in Britain, the USA, Japan, and Korea are presented, and high confidence levels are presented.
Journal ArticleDOI
Outdoor recognition at a distance by fusing gait and face
Zongyi Liu,Sudeep Sarkar +1 more
TL;DR: The combination of outdoor gait and one outdoor face per person is superior to using two outdoor face probes per person or using two gait probes per people, which can considered to be statistical controls for showing improvement by biometric fusion.
Journal ArticleDOI
Local Gradient Hexa Pattern: A Descriptor for Face Recognition and Retrieval
TL;DR: A local gradient hexa pattern is proposed that identifies the relationship among the reference pixel and its neighboring pixels at different distances across different derivative directions, effectively transforming these relationships into binary micropatterns discriminating inter-class facial images with optimal precision.
References
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Journal ArticleDOI
Eigenfaces for recognition
Matthew Turk,Alex Pentland +1 more
TL;DR: A near-real-time computer system that can locate and track a subject's head, and then recognize the person by comparing characteristics of the face to those of known individuals, and that is easy to implement using a neural network architecture.
Journal ArticleDOI
Face recognition by elastic bunch graph matching
TL;DR: A system for recognizing human faces from single images out of a large database containing one image per person, based on a Gabor wavelet transform, which is constructed from a small get of sample image graphs.
Journal ArticleDOI
The FERET database and evaluation procedure for face-recognition algorithms
TL;DR: The FERET evaluation procedure is an independently administered test of face-recognition algorithms to allow a direct comparison between different algorithms and to assess the state of the art in face recognition.
Journal ArticleDOI
Using discriminant eigenfeatures for image retrieval
D.L. Swets,Juyang Weng +1 more
TL;DR: This paper describes the automatic selection of features from an image training set using the theories of multidimensional discriminant analysis and the associated optimal linear projection, and demonstrates the effectiveness of these most discriminating features for view-based class retrieval from a large database of widely varying real-world objects.
Journal ArticleDOI
Probabilistic visual learning for object representation
Baback Moghaddam,Alex Pentland +1 more
TL;DR: An unsupervised technique for visual learning is presented, which is based on density estimation in high-dimensional spaces using an eigenspace decomposition and is applied to the probabilistic visual modeling, detection, recognition, and coding of human faces and nonrigid objects.