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
An Analysis of Random Projection for Changeable and Privacy-Preserving Biometric Verification
TL;DR: A random-projection (RP)-based method for addressing changeability and privacy protection problems in biometrics-based verification systems is presented and a vector translation method is proposed to improve the changeability of the generated templates.
Journal ArticleDOI
Gait recognition based on shape and motion analysis of silhouette contours
TL;DR: A three-phase gait recognition method that analyses the spatio-temporal shape and dynamic motion characteristics of a human subject's silhouettes to identify the subject in the presence of most of the challenging factors that affect existing gait recognized systems is presented.
Journal ArticleDOI
Robust face recognition using 2D and 3D data: Pose and illumination compensation
TL;DR: Experimental results on a large data set show that template-based face recognition performance is significantly benefited from the application of the proposed normalization algorithms prior to classification.
Journal ArticleDOI
Face Recognition Across Non-Uniform Motion Blur, Illumination, and Pose
TL;DR: A nonuniform blur-robust algorithm that is extended to handle illumination variations by exploiting the fact that the set of all images obtained from a face image by non-uniform blurring and changing the illumination forms a bi-convex set.
Proceedings Article
Biometric image processing and recognition
TL;DR: This work considers two promising image-based biometrics, faces and fingerprints, and provides a critical assessment of the state of the art, suggest future research directions, and identify technological challenges.
References
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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.
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Face recognition by elastic bunch graph matching
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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.