THE UCD COLOUR FACE IMAGE DATABASE FOR FACE DETECTION
DOWNLOAD PAGE
Author: Dr. Prag Sharma, Supervised by:
Dr. Richard B. Reilly
School of Electrical, Electronic and
Mechanical Engineering
College of Engineering, Mathematics and
Physical Sciences
UCD, Dublin
National University of Ireland
UCD Colour Face Image (UCFI) Database
With
increasing research in the area of face detection new methods for detecting
human faces automatically are being developed. However, less attention is being
paid to the development of a standard face image database to evaluate these new
algorithms. We recognize the need for a colour face image database and create
such a database for direct benchmarking of automatic face detection algorithms.
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. A few sample images from
the database are shown below. An excel file with details of each image in the
database is available here
How
to download the UCFI Database
Part I
and II of the UCFI database can be downloaded as follows:
1.
Please Sign the Disclaimer Form and send it to
Prag.Sharma@ucd.ie
2.
Once the disclaimer has been verified. The account
name and password will be forwarded it to you. Use these to download the
database from the link below
3.
You can also download the excel file with details
of each image in the database from here.
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Figure 1.
UCD Colour Face Image Database: Part 1: Colour Images
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Figure 2.
UCD Colour Face Image Database: Part 2: Hand Segmented Results
Existing Face Detection Databases
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Data
Set |
Description |
|
MIT Test Set (Sung and Poggio) [1] |
First set contains 301 frontal and near-frontal mug shots of 71 different people and the second set contains 23 images with 149 faces in complex backgrounds. Most faces are frontal and upright. All images are greyscale. |
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CMU Test Set (Rowley et al.) [2], [3] |
130 images with a total of 507 frontal faces. Face sizes vary. All images are greyscale. Also contains 50 images with a total of 223 faces with 95% of the rotated at an angle of more than 10 degrees. All images are greyscale. |
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CMU Profile Test Set (Schneiderman and Kanade) [4] |
208 images with varying facial expressions and in profile view. The images are greyscale. |
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Kodak Data Set [5] |
80 images with 90% of the faces in frontal view. Wide variety of resolutions and face sizes. The images are in colour. |
[1] K-K. Sung, T. Poggio,
Example-Based Learning for View-Based Human Face Detection, IEEE
Transactions on Pattern Analysis and Machine Intelligence, Vol. 20, No.
1,pp. 39-51, January 1998.
[2] H. Rowley, S. Baluja, T.
Kanade, Neural Network-Based Face Detection, IEEE Transactions on Pattern
Analysis and Machine Intelligence, Vol. 20, No. 1, pp. 23-38 January 1998.
[3] H. Rowley, S. Baluja, T. Kanade, Rotation Invariant Neural
Network-Based Face Detection, IEEE Conf. Computer Vision and Pattern
Recognition, pp. 38-44, 1998.
[4] H. Schneiderman, T. Kanade, A Statistical Method for 3D Object
Detection Applied to Faces and Cars, Proc. IEEE Conference on
Computer Vision and Pattern Recognition, Vol. 1, pp.746-751, 2000.
[5] A. C. Loui, C. N. Judice, S. Liu, An Image Database for Benchmarking of Automatic Face Detection and Recognition Algorithms, Proc. IEEE Conference on Image Processing, Vol. 1, pp.146-150, 1998.
EC-VIP-MC 2003 Submission
A Colour Face Image Database
for Benchmarking of Automatic Face Detection Algorithms (pdf file)
ISSC-2004: Belfast Submission
Performance Evaluation Measures for Face Detection Algorithms
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