The BioID Face Database
The BioID Face Database has been recorded and is published to give all researchers working in the
area of face detection the possibility to compare the quality of their face detection algorithms with others.
It may be used for such purposes without further permission.
During the recording special emphasis has been placed on "real world" conditions.
Therefore the testset features a large variety of illumination, background, and face size.
Some typical sample images are shown below.
Description of the face database
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.
The images are labeled "BioID_xxxx.pgm" where the characters xxxx are replaced by the index of the current image (with leading zeros).
Similar to this, the files "BioID_xxxx.eye" contain the eye positions for the corresponding images.
Image file format
The images are stored in single files using the portable gray map (pgm) data format.
A pgm file contains a data header followed by the image data.
In our case the header consists of four lines of text. In detail:
the first line describes the format of the image data (ASCII/binary). In our files the text "P5" indicates that the data is written in binary form
the second line contains the image width written in text form
the third line keeps the image height also in text form
the fourth line contains the maximum allowed gray value (255 in our images)
The header is followed by a data block containing the image data.
The data is stored line per line from top to bottom using one byte per pixel.
Eye position file format
The eye position files are text files containing a single comment line followed by the x and the y coordinate of the left eye
and the x and the y coordinate of the right eye separated by spaces. Note that we refer to the left eye as the person’s left eye.
Therefore, when captured by a camera, the position of the left eye is on the image’s right and vice versa.
Evaluation of face detection algorithms
To make it possible to compare the quality of different face detection algorithms on the testset we propose the following distance-based quality measure:
Estimate the eye positions with your algorithm and calculate the absolute pixel distance
from the manually set positions so that you receive two distance values.
Choose the larger value and divide by the absolute pixel distance of the two manually set
eye positions so that you become independent from the face’s size in the image.
We call this value relative eye distance.
When calculating this distance for each image you can choose the distribution function
of the relative distances to compare some results with others.
Alternatively we recommend to rate a face as found if the relative distance is equal to or less than 0.25, which corresponds to an accuracy of about half the width of an eye in the image. The detection rate can directly be calculated by dividing the number of correctly found faces by the total number of faces in the dataset.
The results for the BioID face detection algorithms can be found in:
Face Detection Using the Hausdorff Distance
O. Jesorsky, K. Kirchberg, R. Frischholz
In J. Bigun and F. Smeraldi, editors,
Audio and Video based Person Authentication - AVBPA 2001, pages 90-95. Springer, 2001
FGnet markup scheme of the face database
The BioID Face Database is being used within the FGnet project of the european working group on face and gesture recognition.
David Cristinacce and Kola Babalola, PhD students from the department of Imaging Science and Biomedical Engineering at the University of Manchester - ISBE
marked up the images from the Bioid Face Database. They selected several additional feature points, which are very useful for facial analysis and gesture recognition. this data is available for public download here (see download information in the right side).
There are 20 manually placed points on each of your 1521 images.
The markup scheme is as follows:
0 = right eye pupil
1 = left eye pupil
2 = right mouth corner
3 = left mouth corner
4 = outer end of right eye brow
5 = inner end of right eye brow
6 = inner end of left eye brow
7 = outer end of left eye brow
8 = right temple
9 = outer corner of right eye
10 = inner corner of right eye
11 = inner corner of left eye
12 = outer corner of left eye
13 = left temple
14 = tip of nose
15 = right nostril
16 = left nostril
17 = centre point on outer edge of upper lip
18 = centre point on outer edge of lower lip
19 = tip of chin