Facial expression databases
Well-annotated (emotion-tagged) media content of facial behavior is essential for training, testing, and validation of algorithms for the development of expression recognition systems. The emotion annotation can be done in discrete emotion labels or on a continuous scale. Most of the databases are usually based on the basic emotions theory (by Paul Ekman), which assumes the existence of six discrete basic emotions (anger, fear, disgust, surprise, joy, sadness). However, some databases include the emotion tagging in continuous arousal-valence scale. And some databases include the AU activations based on FACS.
In posed expression databases, the participants are asked to display different basic emotional expressions, while in spontaneous expression database, the expressions are natural. Spontaneous expressions differ from posed ones remarkably in terms of intensity, configuration, and duration. Apart from this, synthesis of some AUs are barely achievable without undergoing the associated emotional state. Therefore, in most cases, the posed expressions are exaggerated, while the spontaneous ones are subtle and differ in appearance.
|Database||Facial expression||Number of Subjects||Number of images/videos||Gray/Color||Resolution, Frame rate||Ground truth||Type|
|Extended Cohn-Kanade Dataset (CK+) download||neutral, sadness, surprise, happiness, fear, anger, and disgust||123||593 image sequences (327 sequences having discrete emotion labels)||Mostly gray||640* 490||Facial expression labels and FACS (AU label for final frame in each image sequence)||Posed; spontaneous smiles|
|Japanese Female Facial Expressions (JAFFE) download||neutral, sadness, surprise, happiness, fear, anger, and disgust||10||213 static images||Gray||256* 256||Facial expression label||Posed|
|MMI Database download||43||1280 videos and over 250 images||Color||720* 576||AU label for the image frame with apex facial expression in each image sequence||Posed and Spontaneous|
|Belfast Database download||Set 1 (disgust, fear, amusement, frustration, surprise)||114||570 video clips||Color||720*576||Natural Emotion|
|Set 2 (disgust, fear, amusement, frustration, surprise, anger, sadness)||82||650 video clips||Color|
|Set 3 (disgust, fear, amusement)||60||180 video clips||Color||1920*1080|
|DISFA download||-||27||4,845 video frames||Color||1024*768; 20 fps||AU intensity for each video frame (12 AUs)||Spontaneous|
|Multimedia Understanding Group (MUG) download||neutral, sadness, surprise, happiness, fear, anger, and disgust||86||1462 sequences||Color||896*896, 19fps||Emotion labels||Posed|
|Indian Spontaneous Expression Database (ISED) download||sadness, surprise, happiness, and disgust||50||428 videos||Color||1920* 1080, 50 fps||Emotion labels||Spontaneous|
|Radboud Faces Database (RaFD) download||neutral, sadness, contempt, surprise, happiness, fear, anger, and disgust||67||Three different gaze directions and five camera angles (8*67*3*5=8040 images)||Color||681*1024||Emotion labels||Posed|
|FERG (Facial Expression Research Group Database)-DB for stylized characters||angry, disgust, fear, joy, neutral, sad, surprise||6||55767||Color||768x768||Emotion labels||Frontal pose|
- "collection of emotional databases".
- "facial expression databases".
- P. Lucey, J. F. Cohn, T. Kanade, J. Saragih, Z. Ambadar and I. Matthews, "The Extended Cohn-Kanade Dataset (CK+): A complete facial expression dataset for action unit and emotion-specified expression," in 3rd IEEE Workshop on CVPR for Human Communicative Behavior Analysis, 2010
- M. J. Lyons, M. Kamachi and J. Gyoba, "Japanese Female Facial Expressions (JAFFE)," Database of digital images, 1997
- M. Valstar and M. Pantic, "Induced disgust, happiness and surprise: an addition to the MMI facial expression database," in Proc. Int. Conf. Language Resources and Evaluation, 2010
- I. Sneddon, M. McRorie, G. McKeown and J. Hanratty, "The Belfast induced natural emotion database," IEEE Trans. Affective Computing, vol. 3, no. 1, pp. 32-41, 2012
- S. M. Mavadati, M. H. Mahoor, K. Bartlett, P. Trinh and J. Cohn., "DISFA: A Spontaneous Facial Action Intensity Database," IEEE Trans. Affective Computing, vol. 4, no. 2, pp. 151–160, 2013
- N. Aifanti, C. Papachristou and A. Delopoulos, The MUG Facial Expression Database, in Proc. 11th Int. Workshop on Image Analysis for Multimedia Interactive Services (WIAMIS), Desenzano, Italy, April 12–14, 2010.
- S L Happy, P. Patnaik, A. Routray, and R. Guha, “The Indian Spontaneous Expression Database for Emotion Recognition,” in IEEE Transactions on Affective Computing, 2016, doi:10.1109/TAFFC.2015.2498174.
- Langner, O., Dotsch, R., Bijlstra, G., Wigboldus, D.H.J., Hawk, S.T., & van Knippenberg, A. (2010). Presentation and validation of the Radboud Faces Database. Cognition & Emotion, 24(8), 1377—1388. doi:10.1080/02699930903485076
- "Facial Expression Research Group Database (FERG-DB)". grail.cs.washington.edu. Retrieved 2016-12-06.