Face Databases From Other Research Groups
We list some face databases widely used for face related studies, and summarize the specifications of these databases as below.
1. Caltech Occluded Face in the Wild (COFW).
o Source: The COFW face dataset is built by California Institute of Technology,
o Purpose: COFW face dataset contains images with severe facial occlusion. The images are collected from the internet.
o Properties:
Properties | Descriptions |
# of subjects | - |
# of images/videos | 1345 images in the training set and 507 images in the testing set. |
Static/Videos | Static images. |
Single/Multiple faces | Single |
Gray/Color | color |
Resolution | - |
Face pose | Various poses |
Facial expression | Various expressions. |
Illumination | Various illuminations |
3D data | - |
Ground truth | 29 facial landmark and landmark occlusion annotations |
o Reference: refer to the paper: X. P. Burgos-Artizzu, P. Perona and P. Doll�r, "Robust face landmark estimation under occlusion", ICCV 2013, Sydney, Australia, December 2013.
2. Ibug 300 Faces In-the-Wild (ibug 300W) Challenge database.
o Source: The ibug 300W face dataset is built by the Intelligent Behavior Understanding Group (ibug) at Imperial College London,
o Purpose: The ibug 300W face dataset contains ''in-the-wild'' images collected from the internet.
o Properties:
Properties | Descriptions |
# of subjects | - |
# of images/videos | About 4000+ images. |
Static/Videos | Static images. |
Single/Multiple faces | Single |
Gray/Color | color |
Resolution | - |
Face pose | Various poses |
Facial expression | Various expressions. |
Illumination | Various illuminations |
3D data | - |
Ground truth | 68 facial landmark annotations |
o Reference: refer to the paper: C. Sagonas, E. Antonakos, G, Tzimiropoulos, S. Zafeiriou, M. Pantic, ''300 faces In-the-wild challenge: Database and results'', Image and Vision Computing (IMAVIS), 2016.
3. Ibug 300 Videos in the Wild (ibug 300-VW) Challenge dataset.
o Source: The ibug 300VW face dataset is built by the Intelligent Behavior Understanding Group (ibug) at Imperial College London,
o Purpose: The ibug 300VW face dataset contains ''in-the-wild'' videos collected from the internet.
o Properties:
Properties | Descriptions |
# of subjects | - |
# of images/videos | 114 videos. |
Static/Videos | Videos. |
Single/Multiple faces | Single |
Gray/Color | color |
Resolution | - |
Face pose | Various poses |
Facial expression | Various expressions. |
Illumination | Various illuminations |
3D data | - |
Ground truth | 68 facial landmark annotations |
o Reference: refer to the paper: J.Shen, S.Zafeiriou, G. S. Chrysos, J.Kossaifi, G.Tzimiropoulos, and M. Pantic. The first facial landmark tracking in-the-wild challenge: Benchmark and results. In IEEE International Conference on Computer Vision Workshops (ICCVW), 2015.
4. 3D Face Alignment in the Wild (3DFAW) Challenge dataset.
o Source: The 3DFAW dataset is built by Organizers of the 3DFAW challenge,
o Purpose: The 3DFAW face dataset contains real and synthetic facial images with 3D facial landmark annotations.
o Properties:
Properties | Descriptions |
# of subjects | - |
# of images/videos | 10K+ images. |
Static/Videos | Static images. |
Single/Multiple faces | Single |
Gray/Color | color |
Resolution | - |
Face pose | Various poses |
Facial expression | Various expressions. |
Illumination | Various illuminations |
3D data | 3D facial landmark annotations |
Ground truth | 66 3D facial landmark annotations |
o Reference: refer to the website: http://mhug.disi.unitn.it/workshop/3dfaw/.
5. Binghamton University facial expression databases.
o Source: The Binghamton University facial expression databases are built by Dr. Lijun Yin at Binghamton University and other collaborators,
o Purpose: The Binghamton University facial expression databases record images or videos of subjects with various facial expressions. There are multiple types of subsets. Some subsets contain 4D facial data. Some subsets contain multi-modality facial data.
o Properties:
Properties | Descriptions |
# of subjects | Number of subjects varies with different data subsets. |
# of images/videos | - |
Static/Videos | Static and videos. |
Single/Multiple faces | Single |
Gray/Color | color |
Resolution | - |
Face pose | - |
Facial expression | Various expressions. |
Illumination | - |
3D data | 3D face scann |
Ground truth | Facial expression and facial action unit annotations. Some data subsets contain tracked facial landmark locations. |
o Reference: refer to the website: http://www.cs.binghamton.edu/~lijun/Research/3DFE/3DFE_Analysis.html
6. Gaze Interaction For Everybody (GI4E) dataset.
o Source: The GI4E dataset is built by GI4E group,
o Purpose: The GI4E dataset contains facial videos with continuous head pose annotations.
o Properties:
Properties | Descriptions |
# of subjects | 10 |
# of images/videos | 120 videos. |
Static/Videos | Videos. |
Single/Multiple faces | Single |
Gray/Color | color |
Resolution | - |
Face pose | Various poses |
Facial expression | - |
Illumination | - |
3D data | - |
Ground truth | head pose annotations |
o Reference: refer to the paper: Mikel Ariz, Jos� J. Bengoechea, Arantxa Villanueva, Rafael Cabeza, A novel 2D/3D database with automatic face annotation for head tracking and pose estimation, Computer Vision and Image Understanding, Volume 148, July 2016, Pages 201-210
7. Boston University (BU) head tracking dataset.
o Source: The BU head tracking dataset is built by the image and video computing group at Boston University,
o Purpose: The BU head tracking dataset contains facial videos with continuous head pose annotations.
o Properties:
Properties | Descriptions |
# of subjects | 7 |
# of images/videos | 70+ videos |
Static/Videos | Videos |
Single/Multiple faces | Single |
Gray/Color | color |
Resolution | 320*240 |
Face pose | Various poses |
Facial expression | - |
Illumination | Uniform and varying lighting subsets |
3D data | - |
Ground truth | Continuous head pose annotations |
o Reference: refer to the paper: M. La Cascia, S. Sclaroff, and V. Athitsos, "Fast, Reliable Head Tracking under Varying Illumination: An Approach Based on Robust Registration of Texture-Mapped 3D Models", IEEE Trans. Pattern Analysis and Machine Intelligence (PAMI), 22(4), April, 2000.
o Source: The AFEW and SFEW databases are built by Australian National University, University of Canberra, and Commonwealth Scientific and Industrial Research Organisation, Australia ,
o Purpose: Acted Facial Expressions In The Wild (AFEW) is a dynamic temporal facial expressions data corpus consisting of close to real world environment extracted from movies. Static Facial Expressions in the Wild (SFEW) has been developed by selecting frames from AFEW.
o Properties:
Properties | Descriptions |
# of subjects | 330 |
# of images/videos | 1426 video sequences in AFEW database. 700 images in SFEW database (SPI category). |
Static/Videos | Videos in AFEW, Static images in SFEW. |
Single/Multiple faces | Multiple |
Gray/Color | color |
Resolution | - |
Face pose | Various poses |
Facial expression | Angry, Disgust, Fear, Happy, Neutral, Sad, Surprise. |
Illumination | Various illuminations |
3D data | coarse head pose label |
Ground truth | 5 facial landmark annotations for some images |
o Reference: refer to the paper: Abhinav Dhall, Roland Goecke, Simon Lucey, Tom Gedeon, Collecting Large, "Richly Annotated Facial-Expression Databases from Movies", IEEE Multimedia 2012. Abhinav Dhall, Roland Goecke, Simon Lucey, and Tom Gedeon, "Static Facial Expressions in Tough Conditions: Data, Evaluation Protocol And Benchmark", First IEEE International Workshop on Benchmarking Facial Image Analysis Technologies BeFIT, IEEE International Conference on Computer Vision ICCV2011, Barcelona, Spain, 6-13 November 2011.
9. LFW (Labeled Faces in the Wild) Database
o Source: The LFW is built by University of Massachusetts, Amherst,
o Purpose: LFW is a database of face photographs designed for studying the problem of unconstrained face recognition. Variation in clothing, pose, background, and other variables is large in LFW.
o Properties:
Properties | Descriptions |
# of subjects | 5749 |
# of images/videos | 13,233 |
Static/Videos | Static |
Single/Multiple faces | Single |
Gray/Color | color |
Resolution | 250*250 |
Face pose | Various poses |
Facial expression | Various expressions |
Illumination | Various illuminations |
3D data | N/A |
Ground truth | Identifications of subjects |
o Reference: refer to the paper: Gary B. Huang, Manu Ramesh, Tamara Berg, and Erik Learned-Miller, "Labeled Faces in the Wild: A Database for Studying Face Recognition in Unconstrained Environments",
University of Massachusetts, Amherst, Technical Report 07-49, October, 2007.
10. Annotated Facial Landmarks in the Wild (AFLW) database
o Source: The AFLW is built by Graz University of Technology ,
o Purpose: Annotated Facial Landmarks in the Wild (AFLW) provides a large-scale collection of annotated face images gathered from Flickr, exhibiting a large variety in appearance (e.g., pose, expression, ethnicity, age, gender) as well as general imaging and environmental conditions.
o Properties:
Properties | Descriptions |
# of subjects | - |
# of images/videos | 25,993 |
Static/Videos | Static |
Single/Multiple faces | Multiple |
Gray/Color | color |
Resolution | High resolution |
Face pose | Various poses |
Facial expression | Various expressions |
Illumination | Various illuminations |
3D data | coarse head pose estimation |
Ground truth | 21 point markup |
o Reference: refer to the paper: Martin Koestinger, Paul Wohlhart, Peter M. Roth, and Horst Bischof, "Annotated Facial Landmarks in the Wild: A Large-scale, Real-world Database for Facial Landmark Localization", In First IEEE International Workshop on Benchmarking Facial Image Analysis Technologies, 2011.
11. Labeled Face Parts in the Wild (LFPW) Dataset
o Source: The LFPW database is built by Kriegman-Belhumeur Vision Technologies, LLC.
o Purpose: LFPW was used to evaluate a face part (facial fiducial point) detection method. Release 1 of LFPW consists of 1,432 faces from images downloaded from the web using simple text queries on sites such as google.com, flickr.com, and yahoo.com. Each image was labeled by three MTURK workers, and 29 fiducial points are included in dataset.
o Properties:
Properties | Descriptions |
# of subjects | - |
# of images/videos | 1432 |
Static/Videos | Static |
Single/Multiple faces | Single |
Gray/Color | color |
Resolution | - |
Face pose | Various poses |
Facial expression | Various expressions |
Illumination | Various illuminations |
3D data | N/A |
Ground truth | Annotated 29 fiducial points |
o Reference: refer to the paper : Peter N. Belhumeur, David W. Jacobs, David J. Kriegman, and Neeraj Kumar, �Localizing Parts of Faces Using a Consensus of Exemplars,� Proceedings of the 24th IEEE Conference on Computer Vision and Pattern Recognition (CVPR). Additional annotations can be found here: "http://ibug.doc.ic.ac.uk/resources".
12. Helen dataset
o Source: The Helen database is built by The Image Formation & Processing (IFP) Group at the University of Illinois, people from Adobe Systems Inc. and Facebook Inc.
o Purpose: Helen database provides a large-scale collection of annotated facial images gathered from Flickr, exhibiting a large variety in appearance (e.g., pose, expression, ethnicity, age, gender) as well as general imaging and environmental conditions..
o Properties:
Properties | Descriptions |
# of subjects | - |
# of images/videos | 2000 training and 330 testing |
Static/Videos | Static |
Single/Multiple faces | Single |
Gray/Color | color |
Resolution | High resolution |
Face pose | Various poses |
Facial expression | Various expressions |
Illumination | Various illuminations |
3D data | N/A |
Ground truth | Annotated 194 facial landmarks |
o Reference: refer to the paper:Vuong Le, Jonathan Brandt, Zhe Lin, Lubomir Boudev, and Thomas S. Huang, �Interactive Facial Feature Localization�, ECCV2012. Additional annotations can be found here: "http://ibug.doc.ic.ac.uk/resources".
13. The Facial Recognition Technology (FERET) Database
o Source: the FERET database is sponsored by the Defense Advanced Research Products Agency (DARPA).
o Purpose: the FERET database is widely used as the standard face database to evaluate the face recognition systems. It may also be used for face pose estimation and eye detection.
o Properties:
Properties | Descriptions |
# of subjects | 1199 |
# of images/videos | 14051 |
Static/Videos | Static |
Single/Multiple faces | Single |
Gray/Color | eight-bit gray |
Resolution | 256*384 |
Face pose | 7 categories: Frontal, quarter-left, quarter-right, half-left, half-right, full-left, full-right |
Facial expression | Slight facial expression changes |
Illumination | Controlled illumination |
3D data | N/A |
Ground truth | Positions of eyes, nose, and mouth Identifications of subjects |
o Reference: refer to the paper �P. J. Phillips, Hyeonjoon Moon, S. A. Rizvi, and P. J. Rauss, The FERET evaluation methodology for face recognition algorithm, IEEE Trans. on PAMI, vol. 22, no. 10, pp. 1090-1104, October 2000� and the online document �http://www.itl.nist.gov/iad/humanid/feret/feret_master.html�.
14. Face Recognition Grand Challenge (FRGC) Database
o Source: the FRGC database is jointly sponsored by several government agencies interested in improving the capabilities of face recognition technology.
o Purpose: the primary goal of the FRGC database is to evaluate face recognition technology. It may also be used for eye detection.
o Properties:
Properties | Descriptions |
# of subjects | 222 (large still training set) 466 (validation set) |
# of images/videos | 12,776 (large still training set) 943 *8 (3D training set) 4007 *8 (validation set) |
Static/Videos | Static |
Single/Multiple faces | Single |
Gray/Color | Color |
Resolution | 1704*2272 or 1200*1600 |
Face pose | Frontal view |
Facial expression | Neutral and smiling |
Illumination | Controlled and uncontrolled illumination |
3D data | Yes (range and texture) |
Ground truth | Positions of eyes, nose, and mouth Identifications of subjects |
o Reference: Please refer to the paper �P. J. Phillips, P. J. Flynn, T. Scruggs, K. W. Bowyer, J. Chang, K. Hoffman, J. Marques, J. Min, and W. Worek, Overview of the face recognition grand challenge, Proc. of CVPR05, no. 1, pp. 947�954, June 2005� and the original document under the directory �BEE_DISTdoc�.
o Source: CAS-PEAL database is obtained from Chinese Academy of Science.
o Purpose: CAS-PEAL database is used to evaluate the face recognition systems. It may also be used for eye detection, face pose estimation, and facial expression recognition.
o Properties:
Properties | Descriptions |
# of subjects | 1040 (595 males and 445 females) of Asians |
# of images/videos | 30,900 |
Static/Videos | Static |
Single/Multiple faces | Single |
Gray/Color | eight-bit gray |
Resolution | 360*480 |
Face pose | 21 pose angles vertical: up, middle, and down horizontal: left to right (67�, 45�, 22�, 0�, -22�, -45�, -67�) |
Facial expression | 6 facial expressions: neutral, eye closing, frown, smile, surprise, and mouth open |
Illumination | 15 lighting conditions |
Accessories | 3 kinds of glasses and 3 kinds of caps |
3D data | N/A |
Ground truth | Positions of eyes Identifications of subjects Face pose angles Facial expression labels Illumination positions |
o Reference: Please refer to the technical report JDL-TR-04-FR-001 �The CAS-PEAL Large-Scale Chinese Face Database and Baseline Evaluations�.
o Source: The PIE database is obtained from the Robotics Institute of Carnegie Mellon University.
o Purpose: PIE database is used to evaluate the face recognition systems. It may also be used for facial feature detection, face pose estimation, and facial expression recognition.
o Properties:
Properties | Descriptions |
# of subjects | 68 |
# of images/videos | 41,368 |
Static/Videos | Static |
Single/Multiple faces | Single |
Gray/Color | Color |
Resolution | 640*486 |
Face pose | 13 pose angles in vertical and horizontal |
Facial expression | 4 facial expressions: neutral, eye closing, smiling, and talking |
Illumination | N/A |
Accessories | Glasses |
3D data | N/A |
Ground truth | Some feature point data Identifications of subjects Measured locations of camera Head pose Facial expression labels Illumination positions |
Additional materials | Background images |
o Reference: Please refer to the CMU Technical Report CMU-RI-TR-01-02 �The CMU Pose, Illumination, and Expression (PIE) Database of Human Faces�.
- CMU Face Database (Frontal and Profile)
o Source: this database is obtained from the Robotics Institute of Carnegie Mellon University. It combines images collected at CMU and MIT.
o Purpose: this database is primarily used for face detection task. It may also be used for eye detection and facial feature detection.
o Properties:
Properties | Descriptions |
# of subjects | N/A |
# of images/videos | 169 frontal-view face images 202 profile face images |
Static/Videos | Static |
Single/Multiple faces | Multiple |
Gray/Color | eight-bit gray |
Resolution | N/A |
Face pose | Frontal and profile |
Facial expression | Various facial expressions |
Illumination | Various lighting conditions |
Accessories | Various |
3D data | N/A |
Ground truth | Positions of eyes, nose tip, mouth corners, and mouth center for each face (frontal-view face); Positions of eye corner, eye, nose, nose tip, mouth corner, mouth center, chin, earlobe, and ear tip for each face (profile face) |
o Source: this database is constructed by Yale University.
o Purpose: this database can be used for face recognition and facial expression recognition.
o Properties:
Properties | Descriptions |
# of subjects | 15 |
# of images/videos | 165 |
Static/Videos | Static |
Single/Multiple faces | Single |
Gray/Color | eight-bit gray |
Resolution | 320*243 |
Face pose | Frontal view |
Facial expression | 6 facial expressions: neutral, happiness, sadness, sleepiness, surprise, and wink |
Illumination | 3 lighting conditions: center-light, left-light, and right-light |
Accessories | Glasses |
3D data | N/A |
Ground truth | Identifications of subjects Facial expression labels Illumination positions |
o Reference: Please refer to the paper �P. N. Belhumeur, J. P. Hespanha, and D. J. Kriegman, Eigenfaces vs. Fisherfaces: Recognition using class specific linear projection, IEEE Trans. on PAMI, vol. 19, no. 7, pp. 711-720, July 1997�.
o Source: this database is constructed by Yale University.
o Purpose: this database can be used for face recognition, face pose estimation, and eye detection.
o Properties:
Properties | Descriptions |
# of subjects | 10 |
# of images/videos | 5760 |
Static/Videos | Static |
Single/Multiple faces | Single |
Gray/Color | Gray |
Resolution | 640*480 (eye distance ~ 90pixels) |
Face pose | 9 poses |
Facial expression | Neutral |
Illumination | 64 lighting conditions and 1 ambient illumination |
Accessories | N/A |
3D data | N/A |
Ground truth | Identifications of subjects Face pose Illumination positions Coordinates of eyes and mouth (frontal view) Coordinates of face center (other views) |
o Reference: Please refer to the paper �A. S. Georghiades and P. N. Belhumeur, From Few to Many: Illumination Cone Models for Face Recognition under Variable Lighting and Pose, IEEE Trans. on. PAMI, vol.23, no.6, pp.643-660, June 2001�.
o Source: this database is constructed by Georgia Institute of Technology.
o Purpose: this database is primarily used for face recognition. It may also be used for face detection.
o Properties:
Properties | Descriptions |
# of subjects | 50 |
# of images/videos | 750 |
Static/Videos | Static |
Single/Multiple faces | Single |
Gray/Color | color |
Resolution | 640*480 |
Face pose | Nearly frontal-view or quarter-profile images |
Facial expression | Various |
Illumination | Various |
Accessories | Glasses |
3D data | N/A |
Ground truth | Identifications of subjects Coordinates of left-upper corner and right-bottom corner of face rectangle |
o Source: this database is constructed by Aleix Martinez and Robert Benavente in the Computer Vision Center (CVC) at the UAB.
o Purpose: this database is primarily used for face recognition. It may also be used for facial expression recognition.
o Properties:
Properties | Descriptions |
# of subjects | 126 (70 male and 56 female) |
# of images/videos | 4000 |
Static/Videos | Static images and image sequences |
Single/Multiple faces | Single |
Gray/Color | color |
Resolution | 768*576 |
Face pose | Nearly frontal-view or quarter-profile images |
Facial expression | 4 facial expressions: neutral, smile, anger, and scream |
Illumination | 3 illumination conditions: left, right, and all side lights on |
Accessories | Sun glasses, scarf |
3D data | N/A |
Ground truth | Identifications of subjects Facial expression labels |
o Reference: Please refer to the technical report �A. M. Martinez and R. Benavente, The AR Face Database, CVC Technical Report #24, June 1998�.
o Source: this database was constructed by the University of Manchester Institute of Science and Technology that merged with the Victoria University of Manchester to form the University of Manchester.
o Purpose: this database is primarily used for face recognition.
o Properties:
Properties | Descriptions |
# of subjects | 20 |
# of images/videos | 564 |
Static/Videos | Static |
Single/Multiple faces | Single |
Gray/Color | Eight-bit gray |
Resolution | 92*112 |
Face pose | From profile to frontal views |
Facial expression | neutral |
Illumination | N/A |
Accessories | Glasses |
3D data | N/A |
Ground truth | Cropped face region Identifications of subjects |
o Reference: Please refer to the paper �Daniel B Graham and Nigel M Allinson, Characterizing Virtual Eigensignatures for General Purpose Face Recognition, Face Recognition: From Theory to Applications, NATO ASI Series F, Computer and Systems Sciences, vol. 163,
H. Wechsler, P. J. Phillips, V. Bruce, F. Fogelman-Soulie and T. S. Huang (eds), pp. 446-456, 1998�.
o Source: this database is constructed by AT&T Laboratories Cambridge.
o Purpose: this database is primarily used for face recognition.
o Properties:
Properties | Descriptions |
# of subjects | 40 |
# of images/videos | 400 |
Static/Videos | Static |
Single/Multiple faces | Single |
Gray/Color | Eight-bit gray |
Resolution | 92*112 |
Face pose | Moderate pose variation (up and down, quarter-profile to frontal-view) |
Facial expression | 3 facial expressions: neutral, smiling, closed eye |
Illumination | N/A |
Accessories | Glasses |
3D data | N/A |
Ground truth | Cropped face region Identifications of subjects |
o Reference: Please refer to the paper �F. S. Samaria and A. C. Harter �Parameterisation of a stochastic model for human face identification�, Proc. of 2nd IEEE workshop on Applications of Computer Vision, pp. 138-142, 1994�.
o Source: this database is constructed by Center for Biological and Computational Learning at MIT.
o Purpose: this database is primarily used for face detection.
o Properties:
Properties | Descriptions |
# of subjects | N/A |
# of images/videos | Training set: 2,429 faces and 4,548 non-faces Test set: 472 faces and 23,573 non-faces. |
Static/Videos | Static |
Single/Multiple faces | Single |
Gray/Color | Eight-bit gray |
Resolution | 19*19 |
Face pose | Moderate pose variation |
Facial expression | Moderate facial expression changes |
Illumination | Moderate illumination variation |
Accessories | Glasses |
3D data | N/A |
Ground truth | Cropped face region |
o Source: this database is obtained from http://www-prima.inrialpes.fr/Pointing04/data-face.html .
o Purpose: this database is primarily used for face pose estimation task. It may also be used for face recognition.
o Properties:
Properties | Descriptions |
# of subjects | 15 |
# of images/videos | 2790 |
Static/Videos | Static |
Single/Multiple faces | Single |
Gray/Color | Color |
Resolution | 384*288 |
Face pose | Vertical: -90, -60, -30, -15, 0, +15, +30, +60 +90 Horizontal: -90, -75, -60, -45, -30, -15, 0, +15, +30, +45, +60, +75, +90 |
Facial expression | Neutral |
Illumination | N/A |
Accessories | Glasses |
3D data | N/A |
Ground truth | Identifications of subjects Face pose angles |
o Reference: Please refer to the paper �N. Gourier, D. Hall, and J. L. Crowley, �Estimating Face Orientation from Robust Detection of Salient Facial Features,� Proc. of Pointing 2004, ICPR, International Workshop on Visual Observation of Deictic Gestures�.
o Source: this database is constructed by the University of Washington Graphics and Imaging Laboratory.
o Purpose: this database is primarily used for face modeling and animation.
o Properties: 384 face meshes, each with about 23K vertices.
o Reference: Please refer to the paper �Li Zhang, Noah Snavely, Brian Curless, and Steve Seitz, �Spacetime Faces: High-resolution capture for modeling and animation,� Proc. of ACM SIGGRAPH2004�.
o Source: this database is constructed by HumanScan company.
o Purpose: this database can be used for face detection, face recognition and eye detection.
o Properties:
Properties | Descriptions |
# of subjects | 23 |
# of images/videos | 1521 |
Static/Videos | Static |
Single/Multiple faces | Single |
Gray/Color | Gray |
Resolution | 382*288 (eye distance ~ 50pixels) |
Face pose | Frontal |
Facial expression | Various |
Illumination | Various lighting conditions |
Accessories | Various |
3D data | N/A |
Ground truth | Coordinates of eyes. Coordinates of 20 feature points (Eyebrow corners, eye, mouth and tip of chin) |
� Reference: Please refer to the paper �O. Jesorsky, K. Kirchberg, R. Frischholz, Robust Face Detection Using the Hausdorff Distance, Audio and Video based Person Authentication - AVBPA 2001, pages 90-95. Springer, 2001.�.
o Source: this database is constructed by Peter Peer, Computer Vision Laboratory of the University of Ljubljana.
o Purpose: this database can be used for face detection, feature detection, face recognition and 3D face modeling.
o Properties:
Properties | Descriptions |
# of subjects | 114 |
# of images/videos | 798 |
Static/Videos | Static |
Single/Multiple faces | Single |
Gray/Color | Color |
Resolution | 640*480 |
Face pose | Horizontal: -90, -45, 0, 45, 90 |
Facial expression | 3 facial expressions: serious, smiling( showing teeth and showing no teeth) |
Illumination | N/A |
Accessories | N/A |
3D data | N/A |
Ground truth | N/A |
� Reference: Please contact Peter Peer (Peter.peer@fri.uni-lj.si) and Computer Vision Laboratory of the University of Ljubljana for the database.
o Source: this database is constructed by the National Institue of Standards and Technology.
o Purpose: this database is primarily for use in development and testing of automated mugshot identification systems.
o Properties:
Properties | Descriptions |
# of subjects | 1573 (1495 male and 78 female) |
# of images/videos | 3248 |
Static/Videos | Static |
Single/Multiple faces | Single? |
Gray/Color | Gray |
Resolution | Varying in size from 1" - 21/2" in height |
Face pose | front and profile |
Facial expression | N/A |
Illumination | N/A |
Accessories | N/A |
3D data | N/A |
Ground truth | Subject identity |
o Source: this database is collected at the Machine Vision and Media Processing Unit, University of Oulu.
o Purpose: this database can be used for research in face recognition and color.
o Properties:
Properties | Descriptions |
# of subjects | 125 |
# of images/videos | N/A (each person has 16 frontal views and an additional 16 if the person has glasses) |
Static/Video | Static |
Single/Multiple faces | Single |
Gray/Color | Color |
Resolution | 428*569 |
Face pose | Minor various poses |
Facial expression | N/A |
Illumination | Four illuminants: Horizon, Incandescent, Fluorescent and Daylight. |
Accessories | Glasses |
3D data | N/A |
Ground truth | N/A |
� Reference: Please refer to the papsers "A physics-based face database for color research, Journal of Electronic Imaging Vol. 9 No. 1 pp. 32-38." and "Color correction of face images under different illuminants by RGB eigenfaces, Proc. 2nd Audio- and Video-Based Biometric Person Authentication Conference (AVBPA99), March 22-23, Washington DC USA pp. 148-153."
o Source: this database is constructed by the Department of Electronic & Electrical Engineering, University College Dublin. The images are required form a wide variety of sources such as digital cameras, pictures scanned using photo-scanner, other face databases and the world wide web.
o Purpose: this database is primarily to test new face detection algorithms using color information.
o Properties:
Properties | Descriptions |
# of subjects | N/A |
# of images/videos | 299 |
Static/Videos | Static |
Single/Multiple faces | Single? |
Gray/Color | Color |
Resolution | Vaious |
Face pose | Frontal, profile, intermediate, upright and rotated |
Facial expression | Various |
Illumination | Various |
Accessories | Glasses, sunglasses, beards, moustaches |
3D data | N/A |
Ground truth | Hand segmantation |