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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Proceedings ArticleDOI
An angular transform of gait sequences for gait assisted recognition
TL;DR: A new system is proposed for gait analysis and recognition applications based on a denoising process and a new angular transform that are applied on binary silhouettes that improve performance in comparison to other methods of similar or higher complexity.
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An easy game for frauds? Effects of professional experience and time pressure on passport-matching performance.
TL;DR: Time pressure (especially the global time limit) significantly impaired matching performance and the effects of manipulating specific facial features and of variations in the physical distance between the faces being matched were investigated.
Proceedings ArticleDOI
Relative ranking of facial attractiveness
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A local multiple patterns feature descriptor for face recognition
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TL;DR: A local multiple patterns feature descriptor based on the Weber's law for feature extraction and face recognition and a multi-scale block LMP is presented to generate more discriminative and robust visual feature.
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A comparative study of preprocessing mismatch effects in color image based face recognition
TL;DR: A comparative study that addresses the impact of a preprocessing mismatch on color-image based FR methods and explores three different types of preprocessing mismatches, which practical color-based FR system are highly likely to encounter.
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.