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
More filters
ReportDOI
FRVT 2006 and ICE 2006 large-scale results
P. Jonathon Phillips,W. Todd Scruggs,Alice J. O'Toole,Patrick J. Flynn,Kevin W Boyer,Cathy L. Schott,Matthew Sharpe +6 more
TL;DR: On the FRVT 2006 and the ICE 2006 datasets, recognition performance was comparable for all three biometrics and the best-performing face recognition algorithms were more accurate than humans.
Book ChapterDOI
FaceTracer: A Search Engine for Large Collections of Images with Faces
TL;DR: The first image search engine based entirely on faces, which shows state-of-the-art classification results compared to previous works, and demonstrates the power of the architecture through a functional, large-scale face search engine.
HumanEva: Synchronized Video and Motion Capture Dataset for Evaluation of Articulated Human Motion
Leonid Sigal,Michael J. Black +1 more
TL;DR: There is a need for common datasets that allow fair comparison between different methods and their design choices to establish the current state of the art, and it is argued that HumanEva-I will become a standard dataset for the evaluation of articulated human motion and pose estimation.
Journal ArticleDOI
Bregman Divergence-Based Regularization for Transfer Subspace Learning
Si Si,Dacheng Tao,Bo Geng +2 more
TL;DR: This paper presents a family of subspace learning algorithms based on a new form of regularization, which transfers the knowledge gained in training samples to testing samples, and minimizes the Bregman divergence between the distribution of training samples and that of testing samples in the selected subspace.
Journal ArticleDOI
Face Recognition Performance: Role of Demographic Information
TL;DR: It is shown that an alternative to dynamic face matcher selection is to train face recognition algorithms on datasets that are evenly distributed across demographics, as this approach offers consistently high accuracy across all cohorts.
References
More filters
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.