Web-based database for facial expression analysis

By Maja Pantic, Michel François Valstar, R. Rademaker, L. Maat. IEEE International Conference on Multimedia and Expo, 2005

1,178 citations recorded by the source corpus.

Subfields: Cognitive Neuroscience, Computer Vision and Pattern Recognition, Experimental and Cognitive Psychology

View Paper: https://www.semanticscholar.org/paper/2a75f34663a60ab1b04a0049ed1d14335129e908

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Citations in the corpus

Affective Body Expression Perception and Recognition: A Survey (2013, neutral): “, [70], [141], [167], [168], [169], [170], [171], [172], [173]), there are fewer databases that”
Fusing audio, visual and textual clues for sentiment analysis from multimodal content (2016, methodology): “For the experiment they used FGNET [52] and MMI [53] datasets.”
The MUG facial expression database (2010, background): “The MMI facial expression database [7] contains mainly posed but also spontaneous expressions of facial behavior.”
Induced Disgust , Happiness and Surprise : an Addition to the MMI Facial Expression Database (2010, background): “While a number of publicly available benchmark databases with posed displays of the six basic emotions exist, and are well studied (Pantic et al., 2005; Lyons et al., 1998; Kanade et al., 2000), there is no equivalent of this for spontaneous basic emotions.”
Human computing and machine understanding of human behavior: a survey (2006, background): “, [60], [33], Humaine-EU-NoE), this remains an open, highly relevant issue.”
Facial expression recognition based on Local Binary Patterns: A comprehensive study (2009, methodology): “We evaluated the Boosted-LBP based SVM approach on another two publicly available databases: the MMI database [57] and the JAFFE database [7].”
Survey on RGB, 3D, Thermal, and Multimodal Approaches for Facial Expression Recognition: History, Trends, and Affect-related Applications (2016, background): “(b) MMI [192], the ﬁrst dataset to contain proﬁle views.”
Automatic Recognition of Facial Actions in Spontaneous Expressions (2006, background): “Two more recent databases also make a major contribution to the field: The MMI database which enables greater temporal analysis as well as profile views [38], as well as the Lin database which contains 3D range data for prototypical expressions at a variety of intensities [30].”
From Facial Expression Recognition to Interpersonal Relation Prediction (2016, background): “MMI (Pantic et al. 2005) 238 sequences from 28 subjects Lab Posed 720 × 576 RGB frames”
Collecting Large, Richly Annotated Facial-Expression Databases from Movies (2012, background): “C Yes 10 No No No M-PIE4 Manual Lab 27.9 C Yes 337 No No No MMI5 Manual Lab 19 62 C Yes 29 Yes No No Paleari11 Manual CTR CTN Yes No No No RU-FACS6 Manual Lab 18 30 C Yes 100 No No No Semaine12 Manual Lab ?”
Automatic Analysis of Facial Affect: A Survey of Registration, Representation, and Recognition (2015, methodology): “JAFFE [86] Yes 6+N - 10 - 213 - - Posed & Non-posed MMI [105], [153] Yes 6+N - @ +T - 75 2,420 484 temp.”
Facial Action Unit Recognition by Exploiting Their Dynamic and Semantic Relationships (2007, methodology): “[13] report an 84 percent average recognition rate on the Cohn-Kanade database while training on MMI facial expression database [39].”
Automatic Analysis of Facial Actions: A Survey (2019, neutral): “AM-FED [117] Induced N/A Various head poses D 10 N N Bosphorous [155] On command 105 subjects 3D multi-pose S 25 N Y BP4D [218] Induced 41 subjects 3D multi-pose D 27 N Y CASME [207] Induced (micro) 35 subjects Near frontal D F Y N CASME II [206] Induced (micro) 26 subjects Near frontal D F Y N Cohn”
Expression, Affect, Action Unit Recognition: Aff-Wild2, Multi-Task Learning and ArcFace (2019, background): “Until recently affective computing has been mostly studied in controlled settings of the environments [14, 25, 39, 47, 48], with limited amount of participants [3, 26, 31, 33, 40], using pre-deﬁned scenarios that users have to follow, depicting posed expressions [1, 28].”
Static facial expression analysis in tough conditions: Data, evaluation protocol and benchmark (2011, background): “The MMI database [19] is a facial expressions database, which contains both images and videos of 75 subjects shot in a lab-controlled environment.”