gray-level frontal view face database comprises 400 images from 200 persons.
There are 71 females and 129 males, each of whom has two images (fa and fb)
with different facial expressions. The fa images are used as gallery for training
while the fb images as probes for testing. All the images are randomly selected
from the FERET face database. No special criterion is set forth for the selection.
FERET face database, please refer: P.J. Phillips, H. Wechsler, J. Huang, and
P.J. Rauss. The FERET database and evaluation procedure for face-recognition
algorithms. Image and Vision Computing, 1998, 16(5): 295-306.
data set have been used in:
J. Wu and Z.-H. Zhou. Face
recognition with one training image per person.
Pattern Recognition Letters, 2002, 23(14): 1711-1719.
S. Chen, J. Liu, and Z.-H. Zhou. Maing
FLDA applicable to face recognition with one sample per person. Pattern Recognition, 2004, 37(7): 1553-1555.
S. Chen, D. Zhang, and Z.-H. Zhou. Enhanced
(PC)2A for face recognition with one training image per person. Pattern Recognition
Letters, 2004, 25(10): 1173-1181.
J. Liu, S. Chen, and Z.-H. Zhou. Progressive
principal component analysis. In: Proceedings of the 1st International Symposium on
Neural Networks (ISNN'04), Dalian, China,
LNCS 3173, 2004, pp.768-773.
X. Tan, S. Chen, Z.-H. Zhou, and F. Zhang. Robust face recognition from a single training image
per person with kernel-based SOM-face.
In: Proceedings of the 1st International
Symposium on Neural Networks (ISNN'04),
Dalian, China, LNCS 3173, 2004, pp.858-863.
D. Zhang, S. Chen, and Z.-H. Zhou. A new face recognition method based on SVD perturbation
for single example image per person.
Applied Mathematics and Computation, 2005, 163(2): 895-907.
X. Tan, S. Chen, Z.-H. Zhou, and
F. Zhang. Recognizing partially occluded, expression variant faces from single
training image per person with SOM and soft kNN ensemble. IEEE Transactions
on Neural Networks, 2005, 16(4):
S. Chen, L. Chen, and Z.-H. Zhou. A
unified SWSI-KAMs framework and performance evaluation on face recognition. Neurocomputing, 2005, 68: 54-69.
D. Zhang and Z.-H. Zhou. (2D)2PCA: 2-directional 2-dimensional
PCA for efficient face representation and recognition.
2005, 69(1-3): 224-231.
D. Zhang, S. Chen, and Z.-H. Zhou.
non-negative matrix factorization for face representation and recognition. In: Proceedings
of the 2nd International Workshop on Analysis and Modeling of Faces and Gestures
(AMFG'05), in conjunction with
ICCV'05, Beijing, China, LNCS 3723, 2005, 350-363.
D. Zhang, Z.-H. Zhou, and S. Chen. Diagonal principal component analysis for face
Recognition, 2006, 39(1): 140-142.
X. Geng and Z.-H. Zhou. Image region selection and ensemble for face
recognition. Journal of Computer Science & Technology, 2006, 21(1): 116-125.
D. Zhang, Z.-H. Zhou, and S. Chen.
Non-negative matrix factorization on kernels. In: Proceedings
of the 9th Pacific Rim International Conference on Artificial Intelligence (PRICAI'06), Guilin, China, LNAI 4099, 2006, 404-412.
D. Zhang, S. Chen, and Z.-H. Zhou.
Recognizing face or object from a single image: Linear vs. kernel
methods on 2D patterns. In:
Proceedings of the Joint IAPR
International Workshops on Structural and Syntactic Pattern Recognition and
Statistical Techniques in Pattern Recognition (S+SSPR'06), in conjunction with ICPR'06, Hong Kong, China, LNCS 4109, 2006,
ATTN: You can feel
free to use the package (for academic purpose only) at your own risk. But before
publishing your results, please send a copy to:
to our license from FERET, we cannot share the raw images. But we give an index
file which lists the filenames of the images so that you can locate them if
you can access the FERET face database.