The ORL Database of Faces

The ORL Database of Faces is set of face images taken between April 1992 and April 1994 at the lab. The database was used in the context of a face recognition project carried out in collaboration with the Speech, Vision and Robotics Group of the Cambridge University Engineering Department.

There are ten different images of each of 40 distinct subjects. For some subjects, the images were taken at different times, varying the lighting, facial expressions (open / closed eyes, smiling / not smiling) and facial details (glasses / no glasses). All the images were taken against a dark homogeneous background with the subjects in an upright, frontal position (with tolerance for some side movement).

The Database of Faces

Our Database of Faces, (formerly 'The ORL Database of Faces'), contains a set of face images taken between April 1992 and April 1994 at the lab. The database was used in the context of a face recognition project carried out in collaboration with the Speech, Vision and Robotics Group of the Cambridge University Engineering Department.

There are ten different images of each of 40 distinct subjects. For some subjects, the images were taken at different times, varying the lighting, facial expressions (open / closed eyes, smiling / not smiling) and facial details (glasses / no glasses). All the images were taken against a dark homogeneous background with the subjects in an upright, frontal position (with tolerance for some side movement). A preview image of the Database of Faces is available.

The files are in PGM format, and can conveniently be viewed on UNIX (TM) systems using the 'xv' program. The size of each image is 92x112 pixels, with 256 grey levels per pixel. The images are organised in 40 directories (one for each subject), which have names of the form sX, where X indicates the subject number (between 1 and 40). In each of these directories, there are ten different images of that subject, which have names of the form Y.pgm, where Y is the image number for that subject (between 1 and 10).

The database can be retrieved from http://www.cl.cam.ac.uk/Research/DTG/attarchive:pub/data/att_faces.tar.Z as a 4.5Mbyte compressed tar file or from http://www.cl.cam.ac.uk/Research/DTG/attarchive:pub/data/att_faces.zip as a ZIP file of similar size.

A convenient reference to the work using the database is the paper Parameterisation of a stochastic model for human face identification. Researchers in this field may also be interested in the author's PhD thesis, Face Recognition Using Hidden Markov Models, available from http://www.cl.cam.ac.uk/Research/DTG/attarchive/pub/data/fsamaria_thesis.ps.Z (~1.7 MB).

When using these images, please give credit to AT&T Laboratories Cambridge.

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Contact information Copyright © 2002 AT&T Laboratories Cambridge

Credit: https://www.cl.cam.ac.uk/research/dtg/attarchive/facedatabase.html

The ORL Database of Faces contains 400 images from 40 distinct subjects. For some subjects, the images were taken at different times, varying the lighting, facial expressions (open / closed eyes, smiling / not smiling) and facial details (glasses / no glasses). All the images were taken against a dark homogeneous background with the subjects in an upright, frontal position (with tolerance for some side movement). The size of each image is 92x112 pixels, with 256 grey levels per pixel.

The p-values of the pairwise one-tailed Wilcoxon rank sum tests on the test set of the LFW face database (sub-image size 32×32).

The average recognition rates (%) and the corresponding standard deviations (%) of different algorithms on the test set of the AR face database with sunglasses and scarf occlusions (sub-image size 32×32).

The p-values of the pairwise one-tailed Wilcoxon rank sum tests on the test set of the AR face database with sunglasses and scarf occlusions (sub-image size 32×32).

The average recognition rates (%) and the corresponding standard deviations (%) of different algorithms under various sub-image sizes on the test set of the Extended YaleB face database.

The p-values of the pairwise one-tailed Wilcoxon rank sum tests on the test set of the Extended YaleB database.

This directory contains benchmark face databases (AR, FERET, GT, ORL, and Yale) used to evaluate our proposed RSSPCA algorithm in comparison with established methods including PCA, PCA-L1, and RSPCA.

The recognition rates on ORL Face Database.