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
Ethnicity identification from face images
Xiaoguang Lu,Anil K. Jain +1 more
TL;DR: Results are promising, indicating that LDA and the proposed ensemble framework have sufficient discriminative power for the ethnicity classification problem and the normalized ethnicity classification scores can be helpful in the facial identity recognition.
Journal ArticleDOI
A collaborative representation based projections method for feature extraction
TL;DR: Experimental results on FERET, AR, Yale face databases and the PolyU finger-knuckle-print database demonstrate that CRP works well in feature extraction and leads to a good recognition performance.
Journal ArticleDOI
Using Biologically Inspired Features for Face Processing
Ethan M. Meyers,Lior Wolf +1 more
TL;DR: A new set of visual features, derived from a feed-forward model of the primate visual object recognition pathway proposed by Riesenhuber and Poggio (R&P Model), is shown to address the complete recognition problem in a biologically plausible way.
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Transductive Face Sketch-Photo Synthesis
TL;DR: A novel transductive face sketch-photo synthesis method that incorporates the given test samples into the learning process and optimizes the performance on these test samples and efficiently optimizes this probabilistic model by alternating optimization.
Proceedings ArticleDOI
Hierarchical Ensemble of Global and Local Classifiers for Face Recognition
TL;DR: A novel face recognition method which exploits both global and local discriminative features, and which encodes the holistic facial information, such as facial contour, is proposed.
References
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