When benchmarking an algorithm it is recommendable to use a standard test data set for researchers to be able to directly compare the results. While there are many databases in use currently, the choice of an appropriate database to be used should be made based on the task given (aging, expressions, lighting etc). Another way is to choose the data set specific to the property to be tested (e.g. how algorithm behaves when given images with lighting changes or images with different facial expressions). If, on the other hand, an algorithm needs to be trained with more images per class (like LDA), Yale face database is probably more appropriate than FERET. Read more: R. Gross, Face Databases, Handbook of Face Recognition, Stan Z. Li and Anil K. Jain, ed., Springer-Verlag, February 2005, 22 pages Here are some face data sets often used by researchers: The FERET program set out to establish a large database of facial images that was gathered independently from the algorithm developers. Dr. Harry Wechsler at George Mason University was selected to direct the collection of this database. The database collection was a collaborative effort between Dr. Wechsler and Dr. Phillips. The images were collected in a semi-controlled environment. To maintain a degree of consistency throughout the database, the same physical setup was used in each photography session. Because the equipment had to be reassembled for each session, there was some minor variation in images collected on different dates. The FERET database was collected in 15 sessions between August 1993 and July 1996. The database contains 1564 sets of images for a total of 14,126 images that includes 1199 individuals and 365 duplicate sets of images. A duplicate set is a second set of images of a person already in the database and was usually taken on a different day. For some individuals, over two years had elapsed between their first and last sittings, with some subjects being photographed multiple times. This time lapse was important because it enabled researchers to study, for the first time, changes in a subject's appearance that occur over a year. Contains 165 grayscale images in GIF format of 15 individuals. There are 11 images per subject, one per different facial expression or configuration: center-light, w/glasses, happy, left-light, w/no glasses, normal, right-light, sad, sleepy, surprised, and wink. Contains 5760 single light source images of 10 subjects each seen under 576 viewing conditions (9 poses x 64 illumination conditions). For every subject in a particular pose, an image with ambient (background) illumination was also captured. A database of 41,368 images of 68 people, each person under 13 different poses, 43 different illumination conditions, and with 4 different expressions. Project - Face In Action (FIA) Face Video Database, AMP, CMU Capturing scenario mimics the real world applications, for example, when a person is going through the airport check-in point. Six cameras capture human faces from three different angles. Three out of the six cameras have smaller focus length, and the other three have larger focus length. Plan to capture 200 subjects in 3 sessions in different time period. For one session, both in-door and out-door scenario will be captured. User-dependent pose and expression variation are expected from the video sequences. AT&T "The Database of Faces" (formerly "The ORL Database of Faces") 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). Cohn-Kanade AU Coded Facial Expression Database Subjects in the released portion of the Cohn-Kanade AU-Coded Facial Expression Database are 100 university students. They ranged in age from 18 to 30 years. Sixty-five percent were female, 15 percent were African-American, and three percent were Asian or Latino. Subjects were instructed by an experimenter to perform a series of 23 facial displays that included single action units and combinations of action units. Image sequences from neutral to target display were digitized into 640 by 480 or 490 pixel arrays with 8-bit precision for grayscale values. Included with the image files are "sequence" files; these are short text files that describe the order in which images should be read. MIT-CBCL Face Recognition Database The MIT-CBCL face recognition database contains face images of 10 subjects. It provides two training sets: 1. High resolution pictures, including frontal, half-profile and profile view; 2. Synthetic images (324/subject) rendered from 3D head models of the 10 subjects. The head models were generated by fitting a morphable model to the high-resolution training images. The 3D models are not included in the database. The test set consists of 200 images per subject. We varied the illumination, pose (up to about 30 degrees of rotation in depth) and the background. Image Database of Facial Actions and Expressions - Expression Image Database 24 subjects are represented in this database, yielding between about 6 to 18 examples of the 150 different requested actions. Thus, about 7,000 color images are included in the database, and each has a matching gray scale image used in the neural network analysis. Face Recognition Data, University of Essex, UK 395 individuals (male and female), 20 images per individual. Contains images of people of various racial origins, mainly of first year undergraduate students, so the majority of indivuals are between 18-20 years old but some older individuals are also present. Some individuals are wearing glasses and beards. NIST Mugshot Identification Database There are images of 1573 individuals (cases) 1495 male and 78 female. The database contains both front and side (profile) views when available. Separating front views and profiles, there are 131 cases with two or more front views and 1418 with only one front view. Profiles have 89 cases with two or more profiles and 1268 with only one profile. Cases with both fronts and profiles have 89 cases with two or more of both fronts and profiles, 27 with two or more fronts and one profile, and 1217 with only one front and one profile. 450 face images. 896 x 592 pixels. JPEG format. 27 or so unique people under with different lighting/expressions/backgrounds. M2VTS Multimodal Face Database (Release 1.00) Database is made up from 37 different faces and provides 5 shots for each person. These shots were taken at one week intervals or when drastic face changes occurred in the meantime. During each shot, people have been asked to count from '0' to '9' in their native language (most of the people are French speaking), rotate the head from 0 to -90 degrees, again to 0, then to +90 and back to 0 degrees. Also, they have been asked to rotate the head once again without glasses if they wear any. The Extended M2VTS Database, University of Surrey, UK Contains four recordings of 295 subjects taken over a period of four months. Each recording contains a speaking head shot and a rotating head shot. Sets of data taken from this database are available including high quality colour images, 32 KHz 16-bit sound files, video sequences and a 3D model. The AR Face Database, Purdue University, USA 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 University of Oulu Physics-Based Face Database Contains 125 different faces each in 16 different camera calibration and illumination condition, an additional 16 if the person has glasses. Faces in frontal position captured under Horizon, Incandescent, Fluorescent and Daylight illuminant .Includes 3 spectral reflectance of skin per person measured from both cheeks and forehead. Contains RGB spectral response of camera used and spectral power distribution of illuminants. The CAS-PEAL face database has been constructed under the sponsors of National Hi-Tech Program and ISVISION. The goals to create the PEAL face database include: providing the worldwide researchers of FR community a large-scale Chinese face database for training and evaluating their algorithms; facilitating the development of FR by providing large-scale face images with different sources of variations, especially Pose, Expression, Accessories, and Lighting (PEAL); advancing the state-of-the-art face recognition technologies aiming at practical applications especially for the oriental. Japanese Female Facial Expression (JAFFE) Database The database contains 213 images of 7 facial expressions (6 basic facial expressions + 1 neutral) posed by 10 Japanese female models. Each image has been rated on 6 emotion adjectives by 60 Japanese subjects. BioID Face DB - HumanScan AG, Switzerland The dataset consists of 1521 gray level images with a resolution of 384x286 pixel. Each one shows the frontal view of a face of one out of 23 different test persons. For comparison reasons the set also contains manually set eye postions. Psychological Image Collection at Stirling (PICS) This is a collection of images useful for research in Psychology, such as sets of faces and objects. The images in the database are organised into SETS, with each set often representing a separate experimental study. Consists of 564 images of 20 people. Each covering a range of poses from profile to frontal views. Subjects cover a range of race/sex/appearance. Each subject exists in their own directory labelled 1a, 1b, ... 1t and images are numbered consequetively as they were taken. The files are all in PGM format, approximately 220 x 220 pixels in 256 shades of grey. Face Video Database of the Max Planck Institute for Biological Cybernetics This database contains short video sequences of facial Action Units recorded simultaneously from six different viewpoints, recorded in 2003 at the Max Planck Institute for Biological Cybernetics. The video cameras were arranged at 18 degrees intervals in a semi-circle around the subject at a distance of roughly 1.3m. The cameras recorded 25 frames/sec at 786x576 video resolution, non-interlaced. In order to facilitate the recovery of rigid head motion, the subject wore a headplate with 6 green markers. The website contains a total of 246 video sequences in MPEG1 format. 450 face images. 896 x 592 pixels. JPEG format. 27 or so unique people under with different lighting/expressions/backgrounds. Human identification from facial features has been studied primarily using imagery from visible video cameras. Thermal imaging sensors are one of the most innovative emerging techonologies in the market. Fueled by ever lowering costs and improved sensitivity and resolution, our sensors provide exciting new oportunities for biometric identification. As part of our involvement in this effort, Equinox is collecting an extensive database of face imagery in the following modalities: coregistered broadband-visible/LWIR (8-12 microns), MWIR (3-5 microns), SWIR (0.9-1.7 microns). This data collection is made available for experimentation and statistical performance evaluations. With the aim to facilitate the development of robust audio, face, and multi-modal person recognition systems, the large and realistic multi-modal (audio-visual) VALID database was acquired in a noisy "real world" office scenario with no control on illumination or acoustic noise. The database consists of five recording sessions of 106 subjects over a period of one month. One session is recorded in a studio with controlled lighting and no background noise, the other 4 sessions are recorded in office type scenarios. The database contains uncompressed JPEG Images at resolution of 720x576 pixels. The UCD Colour Face Image Database for Face Detection The database has two parts. Part one contains colour pictures of faces having a high degree of variability in scale, location, orientation, pose, facial expression and lighting conditions, while part two has manually segmented results for each of the images in part one of the database. These images are acquired from a wide variety of sources such as digital cameras, pictures scanned using photo-scanner, other face databases and the World Wide Web. The database is intended for distribution to researchers. The database contains images of 50 people and is stored in JPEG format. For each individual, there are 15 color images captured between 06/01/99 and 11/15/99. Most of the images were taken in two different sessions to take into account the variations in illumination conditions, facial expression, and appearance. In addition to this, the faces were captured at different scales and orientations. The database contains a set of face images taken in February, 2002 in the IIT Kanpur campus. There are eleven different images of each of 40 distinct subjects. For some subjects, some additional photographs are included. All the images were taken against a bright homogeneous background with the subjects in an upright, frontal position. The files are in JPEG format. The size of each image is 640x480 pixels, with 256 grey levels per pixel. The images are organized in two main directories - males and females. In each of these directories, there are directories with name as a serial numbers, each corresponding to a single individual. In each of these directories, there are eleven different images of that subject, which have names of the form abc.jpg, where abc is the image number for that subject. The following orientations of the face are included: looking front, looking left, looking right, looking up, looking up towards left, looking up towards right, looking down. Available emotions are: neutral, smile, laughter, sad/disgust. The VidTIMIT database is comprised of video and corresponding audio recordings of 43 people, reciting short sentences. It can be useful for research on topics such as multi-view face recognition, automatic lip reading and multi-modal speech recognition. The dataset was recorded in 3 sessions, with a space of about a week between each session. There are 10 sentences per person, chosen from the TIMIT corpus. In addition to the sentences, each person performed a head rotation sequence in each session. The sequence consists of the person moving their head to the left, right, back to the center, up, then down and finally return to center. The recording was done in an office environment using a broadcast quality digital video camera. The video of each person is stored as a numbered sequence of JPEG images with a resolution of 512 x 384 pixels. The corresponding audio is stored as a mono, 16 bit, 32 kHz WAV file. Labeled Faces in the Wild is a database of face photographs designed for studying the problem of unconstrained face recognition. The database contains more than 13,000 images of faces collected from the web. Each face has been labeled with the name of the person pictured. 1680 of the people pictured have two or more distinct photos in the database. The only constraint on these faces is that they were detected by the Viola-Jones face detector. Please see the database web page and the technical report linked there for more details.
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FACE RECOGNITION HOMEPAGE
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© 2005-2008 VCL
Last update: 5 May 2008