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. For sample images please vistit the BioID Face DB page.
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.
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.
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.
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.
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 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.
For more information about the BioID Face Database, sample pictures and a sample of the FGnet Markup Scheme please visit BioID Face DB page.
For more Information about the FGnet Face and Gesture Recognition Working group please visit the FGnet Homepage.