| Face colour under varying illumination - analysis and applications | ||
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Up to date, databases containing many faces have been created employing cameras and some of them contain colour images and even videos. Their main purpose has been to provide material to test and develop face recognition and detection algorithms. If the illumination changes are taken into consideration in these images, it is typically caused by variation in illumination direction, camera viewpoint or different white balancing light sources. Table 1 summarizes the properties of face databases some of which can be even downloaded from the WWW (see links at http://www.ee.oulu.fi/research/imag/color/). Also Yang and Ahuja (2001) and Gong et al. (2000) provide information on some of these databases. The physical basis of image formation data like camera responses are not considered with these databases and in some cases not even the type of the camera is mentioned. The illumination conditions are not reported and in some cases illumination changes are in fact caused by changes in illumination direction. Some databases do contain videos, for example from TV, but they are not taken in real, drastic conditions.
Table 1. Face databases.
| Face database | Number of persons | Images | Variables | Other data related to face |
|---|---|---|---|---|
| MIT (Turk & Pentland 1991) | 16 men | 27 images per person grey images | 1. illumination direction 2. head tilt (orientation) 3. scale | a video sequence of person moving behind a plant |
| Shimon Edelman"s | 28 persons | minimum: 60 images per person grey images | 1. horizontal illumination level 2. viewpoint 3. face expressions (3) | |
| CMU test images for face detection | 3 datasets; 2 test sets not mentioned | grey images | 1. frontal and profile views 2. different backgrounds | ground truths |
| University of Stirling | not mentioned | 1591 colour and grey images | 1. illumination (not defined) 2. expression 3. different views and poses | |
| M2VTS (Pigeon & Vandendrope 1997) | 37 and 295 | 185 and 295colour images | 1. rotation 2. expressions 3. glasses on / off | four video sequences per person (295, head rotation under controlled lighting) and speech data |
| Yale (Belhumeur et al. 1997, Georghiades et al. 2001) | two databases, 15 and 10 | 165 grey images and 5850 grey images | 1. facial expressions 2. glasses on / off 3. lighting direction and level | |
| UMIST (Graham & Allinson 1998) | together 20 men and women | 564grey images | 1. different poses from profile to frontal view | |
| Purdue AR University (Martinez & Benavente 1998) | 126, 70 men and 56 women | over 4000 colour images frontal view | 1. facial expressions 2. occlusions 3. illumination: some images with different direction of yellowish light | |
| Goudail et al. (1996) | 116 | 11600 frontal, grey images | 1. pose | two 30 s moving head videos |
| AT & T (Olivetti) (Samaria & Harter 1994) | 40 | 400 grey images | 1. time 2. lighting level 3. facial expressions 4. glasses on / off | |
| University of Bern | 30 | 450 grey images | 1. head position 2. size 3. contrast | |
| FERET (Phillips et al. 2000) | not mentioned | 14051 grey images | 1. different poses from profiles to frontal view 2. different lighting level 3. facial expressions | ground truths |
| Kodak data set (Loui et al. 1998) | not mentioned | colour | 1. size 2. pose 3. illumination between images (near white balanced ones) | videos (no big skin tone changes) |
| The Japanese Female Facial Expression (JAFFE) Database | 10 women | 213 grey images | 1. facial expressions | emotion ratings |
| PEIPA (Pilot European Image Processing Archive) | two datasets | over 750 colour and grey | 1. pose 2. contrast | |
| Harvard (Hallinan 1995) | 10 | not mentioned grey | 1. illumination direction | |
| Usenix face dataset | not mentioned | 5592 | 1. variable viewing conditions | |
| NISTS Special Database 18 (Mugshot Identification Database) | 1573: 1495 men and 78 women | 3248 grey images | 1. poses: frontal and profile 2. size |