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126 people (over 4,000 color images).
Two sessions per person (2 different days).
This face database was created by Aleix Martinez and Robert Benavente in the Computer Vision Center (CVC) at the U.A.B. It contains over 4,000 color images corresponding to 126 people’s faces (70 men and 56 women). Images feature frontal view faces with different facial expressions, illumination conditions, and occlusions (sun glasses and scarf). The pictures were taken at the CVC under strictly controlled conditions. No restrictions on wear (clothes, glasses, etc.), make-up, hair style, etc. were imposed to participants. Each person participated in two sessions, separated by two weeks (14 days) time. The same pictures were taken in both sessions.
This face database is publicly available and can be obtained from this web-site. It is free for academic use. Commercial distribution or any act related to commercial use of this database is strictly prohibited.
See a movie example (due to compression the quality of this video is not very good):arfd2.avi (1.97 Mb).
All images are stored in 10 different CD-ROMs as RGB RAW files (pixel information). Images are of 768 by 576 pixels and of 24 bits of depth.
Male images are stored as: M-xx-yy.raw
Females as: F-xx-yy.raw
‘xx’ is a unique person identifier (from “00” to “70” for males and from “00” to “56” for females)
‘yy’ specifies the features of each image; its meanings are described at the following table:
1 : Neutral expression
5 : left light on
6 : right light on
7 : all side lights on
8 : wearing sun glasses
9 : wearing sun glasses and left light on
10 : wearing sun glasses and right light on
11 : wearing scarf
12 : wearing scarf and left light on
13 : wearing scarf and right light on
14 to 26 : second session (same conditions as 1 to 13)
A total of 30 sequences of images were also grabbed to test dynamic systems. Each sequence consist of 25 color images (same size as above).
CDs 1 to 8 contain the static images. CDs 9 and 10 contains the sequences.
You can convert images from RAW to any other format using ImageMagick (using convert) or any other image software. Convert is part of the freely available ImageMagick library which runs well under any version of Unix (and functions okay under NT, VMS, MacOS, and OS/2): http://www.wizards.dupont.com/cristy/ImageMagick.html
This is only an example of how the images of the AR face database look like. Images have been reduced in size and except the first one all images have been converted to greyscale images (8 bits) and saved as JPG (with 75 quality rate). To get a real example click here.
How to get a password & terms and conditions
This database is publicly available. It is free for professors and researcher scientists affiliated to a University. All publications and works that use the AR face database must reference the following report: A.M. Martinez and R. Benavente. The AR Face Database. CVC Technical Report #24, June 1998.
Permission to use but not reproduce or distribute the AR face database is granted to all researchers given that the following steps are properly followed:
1. Send an e-mail to Prof. Aleix M. Martinez before downloading the database. You will need a user-name and password to access the files of this database. Your Email MUST be set from a valid University account and must include the following text:
Subject: Application to download the AR Face Database
I have read and agree to the terms and conditions specified in the AR face database webpage. This database will only be used for research purposes. I will not make any part of this database available to a third party. I’ll not sell any part of this database or make any profit from its use.
2. All submitted papers (or any publicly available text) that uses or talks about the AR face database must cite the following report: A.M. Martinez and R. Benavente, “The AR face database,” CVC Tech. Report #24, 1998.
3. Permission is NOT granted to reproduce the database or posted itinto any webpage that is not the AR face database web-page administreted by Prof. Aleix M. Martinez.
4. Written permission must be obtained from Prof. Aleix M. Martinez if a faculty member desires to share the database with her/his co-workers or students. Even then, the database cannot be posted on a web-page accessible from outside the faculty research group.
5. No economical profit can be made from this database.
This database contains human subjects who agreed to participate in the adquisition of this dataset for research purposes. To guarantee the proper use of this database, the above steps are required and must be followed by everyone. No country or institution is excluded of any of the above steps. By downloading this database you agree to abid to these conditions. Failure to follow the above steps will be legally prosecuted.
Downloading the Database
Files below are between 100 and 180 Mb.
Recall: All publications that use the AR face database must reference the following report: A.M. Martinez and R. Benavente. The AR Face Database. CVC Technical Report #24, June 1998.
To obtain a password follow the instructions provided above. Failure to follow these instructions may result in no response. On a general bases, passwords take from 2 to 4 weeks to be issued (be patient). To avoind problems with our firewall, make sure your email is sent from a .edu (or similar) address.
Other (relevant) downloads
1. The face crops (warps) used in the paper “PCA versus LDA” EEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 23, No. 2, pp. 228-233, 2001, can be dowloaded below. You can use the same password for these. Papers using these crops should cite the paper “PCA versus LDA.”
2. Manual Annotations: This file contains four (4) different manual annotations of the shape of each of the facial components of the faces in teh AR database. Detail description of the manual annotations are in: Ding & Martinez, “Features versus Context: An approach for precise and detailed detection and delineation of faces and facial features” PDF.
All paper using these manual annotations must cite the paper “Features versus Context: An approach for precise and detailed detection and delineation of faces and facial features,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 32, No. 11, pp. 2022-2038, 2010.
You can find papers that have used this database in Google-Scholar:
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