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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Face colour under varying illumination - analysis and applications
TL;DR: It was demonstrated that the skin colour model can be used to segment faces and the segmentation results depend on the background due to the method used, and the performances of these adaptive algorithms were superior compared to those using a fixed skin color model or model adaptation based on spatial pixel selection.
Posted Content
A survey of face recognition techniques under occlusion
TL;DR: In this paper, a review of face detection under occlusion, a preliminary step in face recognition, is presented and the authors analyze the motivations, innovations, pros and cons, and the performance of representative approaches.
Proceedings ArticleDOI
Local frequency descriptor for low-resolution face recognition
TL;DR: An effective local frequency descriptor for low resolution face recognition is proposed, by building upon the ideas behind local phase quantization (LPQ) and exploring both blur-invariant magnitude and phase information in the low frequency domain.
Journal ArticleDOI
Rumpling instability in thermal barrier systems under isothermal conditions in vacuum
TL;DR: In this paper, two types of BC-superalloy systems were subjected to isothermal exposure at temperatures ranging from 1150°C to 1200°C in vacuum, and the results showed that the nickel aluminide BC rumpled at 1200°c and at 1175°C, in the absence of significant oxidation.
Proceedings Article
Sobel-LBP
TL;DR: A new Sobel-LBP, an extension of existing local binary pattern (LBP), for facial image representation, which provides a significantly better performance than LBP under various conditions.
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.
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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.