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{{short description|none}}
A '''facial expression database''' is a collection of images or video clips with [[facial expression]]s of a range of [[emotions]].
Well-annotated ([[emotion]]-tagged) media content of facial behavior is essential for training, testing, and validation of [[algorithm]]s for the development of [[Emotion recognition|expression recognition systems]]. The emotion annotation can be done in [[discrete emotion theory|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.
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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.
Many publicly available databases are categorized here.<ref>{{Cite web|url=http://emotion-research.net/wiki/Databases|title=collection of emotional databases|archive-url=https://web.archive.org/web/20180325205102/http://emotion-research.net/wiki/Databases|archive-date=2018-03-25|url-status=dead}}</ref><ref>{{Cite web|url=https://www.ecse.rpi.edu/~cvrl/database/other_facial_expression.htm|title=facial expression databases
{| class="wikitable"
!Database
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!Ground truth
!Type
|▼
|-
|FERG-3D-DB (Facial Expression Research Group 3D Database) for stylized characters <ref>Aneja, Deepali, et al. "Learning to generate 3D stylized character expressions from humans." 2018 IEEE Winter Conference on Applications of Computer Vision (WACV). IEEE, 2018.</ref>
|angry, disgust, fear, joy, neutral, sad, surprise
|4
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|Ryerson Audio-Visual Database of Emotional Speech and Song (RAVDESS) <ref>Livingstone & Russo (2018). The Ryerson Audio-Visual Database of
Emotional Speech and Song (RAVDESS): A dynamic, multimodal set of facial and vocal expressions in North American English. {{doi|10.1371/journal.pone.0196391
|doi-access=free}}</ref>
|Speech: Calm, happy, sad, angry, fearful, surprise, disgust, and neutral.
Song: Calm, happy, sad, angry, fearful, and neutral.
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|Posed
|-
|Extended Cohn-Kanade Dataset (CK+)<ref>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</ref>
|neutral, sadness, surprise, happiness, fear, anger, contempt and disgust
|123
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|Posed; spontaneous smiles
|-
|Japanese Female Facial Expressions (JAFFE)<ref>{{Cite book | doi=10.5281/zenodo.3451524| year=1998| last1=Lyons| first1=Michael| title=The Japanese Female Facial Expression (JAFFE) Database| last2=Kamachi| first2=Miyuki| last3=Gyoba| first3=Jiro}}</ref>
|neutral, sadness, surprise, happiness, fear, anger, and disgust
|10
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|Posed
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|MMI Database<ref>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</ref>
|
|43
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|Posed and Spontaneous
|-
| rowspan="3" |Belfast Database<ref>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</ref>
|Set 1 (disgust, fear, amusement, frustration, surprise)
|114
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|-
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|DISFA<ref>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</ref> [https://web.archive.org/web/20151024114056/http://www.engr.du.edu/mmahoor/DISFA.htm download]▼
|Happy, Sad, Fear, Surprise, Angry, Neutral, Disgust▼
|44
|395 clips▼
|Color
|1920x1080▼
(60 fps)▼
|Emotion labels
|Spontaneous
|-
▲|DISFA<ref>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</ref>
| -
|27
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|Spontaneous
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|Multimedia Understanding Group (MUG)<ref>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.</ref>
|neutral, sadness, surprise, happiness, fear, anger, and disgust
|86
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|Posed
|-
|Indian Spontaneous Expression Database (ISED)<ref>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}}.</ref>
|sadness, surprise, happiness, and disgust
|50
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|Spontaneous
|-
|Radboud Faces Database (RaFD)<ref>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}}</ref>
|neutral, sadness, contempt, surprise, happiness, fear, anger, and disgust
|67
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|Posed
|-
|Oulu-CASIA NIR-VIS database
|surprise, happiness, sadness, anger, fear and disgust
|80
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|Frontal pose
|-
|
|neutral, happy, sad, surprise, fear, disgust, anger, contempt
|
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|Wild setting
|-
|
|neutral frontal, joy, sadness, surprise, anger, disgust, fear, opened, closed, kiss, left side, right side, neutral sagittal left, neutral sagittal right, nape and forehead (acquired sometimes)
|38
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|Posed
|-
|
|neutral,smile
|200
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|Posed
|-
|Aff-Wild
|valence and arousal
▲|
|200
|~1,250,000 manually annotated
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|In-the-Wild setting
|-
|Aff-Wild2<ref>{{Cite journal|last1=Kollias|first1=D.|last2=Zafeiriou|first2=S.|date=2019|title=Expression, affect, action unit recognition: Aff-wild2, multi-task learning and arcface|url=https://bmvc2019.org/wp-content/uploads/papers/0399-paper.pdf|journal=British Machine Vision Conference (BMVC), 2019|arxiv=1910.04855}}</ref><ref>{{Cite book|last1=Kollias|first1=D.|last2=Schulc|first2=A.|last3=Hajiyev|first3=E.|last4=Zafeiriou|first4=S.|title=2020 15th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2020) |chapter=Analysing Affective Behavior in the First ABAW 2020 Competition |date=2020|chapter-url=https://www.computer.org/csdl/proceedings-article/fg/2020/307900a794/1kecIYu9wL6|pages=637–643|doi=10.1109/FG47880.2020.00126|arxiv=2001.11409|isbn=978-1-7281-3079-8|s2cid=210966051}}</ref>
▲|iSAFE (Indian Semi-Acted Facial Expression Database)<ref>{{Cite journal|last=Singh|first=Shivendra|last2=Benedict|first2=Shajulin|date=2020|editor-last=Thampi|editor-first=Sabu M.|editor2-last=Hegde|editor2-first=Rajesh M.|editor3-last=Krishnan|editor3-first=Sri|editor4-last=Mukhopadhyay|editor4-first=Jayanta|editor5-last=Chaudhary|editor5-first=Vipin|editor6-last=Marques|editor6-first=Oge|editor7-last=Piramuthu|editor7-first=Selwyn|editor8-last=Corchado|editor8-first=Juan M.|title=Indian Semi-Acted Facial Expression (iSAFE) Dataset for Human Emotions Recognition|url=https://link.springer.com/chapter/10.1007/978-981-15-4828-4_13|journal=Advances in Signal Processing and Intelligent Recognition Systems|series=Communications in Computer and Information Science|language=en|___location=Singapore|publisher=Springer|pages=150–162|doi=10.1007/978-981-15-4828-4_13|isbn=978-981-15-4828-4}}</ref> [https://github.com/shivendra2015iiit/Indian-Semi-Acted-Facial-Expression-Database-iSAFE-/blob/master/README.md download]
|neutral, happiness, sadness, surprise, fear, disgust, anger + valence-arousal + action units 1,2,4,6,12,15,20,25
▲|Happy, Sad, Fear, Surprise, Angry, Neutral, Disgust
|
|~2,800,000 manually annotated
▲|395 clips
|Color
|Various (average = 1030x630)
▲|1920x1080
|Valence, Arousal, 7 basic expressions, action units for each video frame
▲(60 fps)
|In-the-Wild setting
|-
|Real-world Affective Faces Database (RAF-DB)<ref>{{Cite web|last=Li.|first=S.|title=RAF-DB|url=http://www.whdeng.cn/RAF/model1.html|website=Real-world Affective Faces Database}}</ref><ref>{{Cite book|last1=Li|first1=S.|last2=Deng|first2=W.|last3=Du|first3=J.|title=2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) |chapter=Reliable Crowdsourcing and Deep Locality-Preserving Learning for Expression Recognition in the Wild |date=2017|pages=2584–2593|doi=10.1109/CVPR.2017.277|isbn=978-1-5386-0457-1|s2cid=11413183}}</ref>
|6 classes of '''basic emotions''' (Surprised, Fear, Disgust, Happy, Sad, Angry) plus Neutral and 12 classes of '''compound emotions''' (Fearfully Surprised, Fearfully Disgusted, Sadly Angry, Sadly Fearful, Angrily Disgusted, Angrily Surprised, Sadly Disgusted, Disgustedly Surprised, Happily Surprised, Sadly Surprised, Fearfully Angry, Happily Disgusted)
▲|
|29672 annotated examples
|Color
|Various for original dataset and 100x100 for aligned dataset
|Emotion labels
|Posed and Spontaneous
|-
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{{reflist}}
{{Nonverbal communication}}
[[Category:Database-related lists|Facial expression]]
[[Category:Facial expressions]]
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