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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Book ChapterDOI
On the Effects of Image Alterations on Face Recognition Accuracy
TL;DR: This chapter analyzes the effects of intentional or unintentional face image alterations on face recognition algorithms and the human capabilities to deal with altered images in scenarios where the user template is created from printed photographs rather than from images acquired live during enrollment.
Journal ArticleDOI
A Comprehensive Performance Evaluation of Deformable Face Tracking In-the-Wild
TL;DR: This paper performs the first, to the best of the knowledge, thorough evaluation of state-of-the-art deformable face tracking pipelines using the recently introduced 300 VW benchmark and reveals future avenues for further research on the topic.
ReportDOI
Appearance-Based Facial Recognition Using Visible and Thermal Imagery: A Comparative Study
TL;DR: In this paper, a comprehensive performance analysis of multiple appearance-based face recognition methodologies, on visible and thermal infrared imagery, is presented, comparing algorithms within and between modalities in terms of recognition performance, false alarm rates and requirements to achieve specified performance levels.
Journal ArticleDOI
Learning Regularized LDA by Clustering
TL;DR: This work proposes making use of the structure of the given training data to regularize the between- and within-class scatter matrices by between-and-within-cluster scattermatrices, respectively, and simultaneously, and demonstrates the effectiveness of the proposed method.
Journal ArticleDOI
Component-Based Representation in Automated Face Recognition
TL;DR: It is demonstrated on three public datasets and an operational dataset consisting of face images of 8000 subjects, that the proposed component-based representation provides higher recognition accuracies over holistic-based representations.
References
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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
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D.L. Swets,Juyang Weng +1 more
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Baback Moghaddam,Alex Pentland +1 more
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