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. During the recording special emphasis has been laid 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 BioID 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 give the possibility 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
postions 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 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 fo the BioID face detection algorithms can be found in a paper that will be published
at the AVBPA01 ((link: http://www.hh.se/avbpa/)) (Audio- and Video-Based Biometric Person Authentication)
conference taking place in Halmstad, Sweden in June 2001.
For recommendations or questions send an e-mail to: research@bioid.com.
BioID人脸数据库(1)
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