RPI ISL Eye Database
Source: this database is collected by our own research group and other
groups.
Purpose: this database is primarily used in eye detection and tracking.
This database includes
the cropped image of left/right eye (open/closed) region of different sizes and
orientations.
Database |
Description |
Blink |
Square images, 2070 closed eye images and
1773 open eye images |
FERET_eye |
Square images, 326 eye images |
FRGC_Eye |
Square images, 22850 eye
images |
FRGC_Eye_Centered |
Rectangular images, 4364 eye
images |
FRGC_pupil |
Square images, 3636 pupil
images with different sizes |
Square images, 131325 images
with same size, where pupil is not in the center of the image |
|
Square images, 3636 images
with different sizes, where pupil is not in the center of the image |
|
Square images, 78475 images
with same size, where pupil is not in the center of the image |
|
Non-eye |
Square images, over 140,000
non-eye images |
The image sequences are taken under IR cameras. Each image sequence is decomposed into dark pupil image sequence and its corresponding bright pupil image sequence.
·
Source: this
database is collected by our own research group. The image sequences are taken
under IR cameras. Each image sequence is decomposed into dark pupil image
sequence and its corresponding bright pupil image sequence.
·
Purpose: this
database is primarily used in eye detection and tracking.
Properties:
Properties |
Descriptions |
# of subjects |
9 |
# of images/videos |
22 |
Static/Videos |
Videos |
Single/Multiple
faces |
Single |
Gray/Color |
Eight-bit gray
images |
Resolution |
320 * 240 |
Face pose |
Various |
Facial expression |
Moderate facial
expression changes |
Illumination |
IR illumination |
Accessories |
N/A |
o Source: this database is created and labeled by the Machine Perception Lab of the University of San Diego, California. Most of the images are collected from the web.
o
Purpose: this database is primarily used for eye detection and
blink detection.
o
Properties:
Properties |
Descriptions |
# of subjects |
N/A |
# of images/videos |
197 for open eye
and 230 for closed eye |
Static/Videos |
Static |
Single/Multiple
faces |
Single |
Gray/Color |
color |
Resolution |
N/A |
Face pose |
Various |
Facial expression |
Various |
Illumination |
Various |
Accessories |
Various |
3D data |
N/A |
Ground truth |
Coordinates of eyes Label of open/close |
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
3.
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
o Source: CAS-PEAL database is obtained from
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 (67º, 45º, 22º, 0º, -22º, -45º, -67º) |
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”.
5. 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
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
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.”.