Children Spontaneous Facial Expression Video Database (LIRIS-CSE),
2019.
Dataset, Facial Expressions.
WWW Link.
spontaneous / natural facial expressions of 12 children in diverse
settings with variable recording scenarios showing six universal or
prototypic emotional expressions (happiness, sadness, anger, surprise,
disgust and fear).
See also novel database of children's spontaneous facial expressions (LIRIS-CSE), A.
Littlewort, G.C.[Gwen C.],
Bartlett, M.S.[Marian Stewart],
Fasel, I.R.[Ian R.],
Susskind, J.[Joshua],
Movellan, J.R.[Javier R.],
Dynamics of Facial Expression Extracted Automatically from Video,
IVC(24), No. 6, 1 June 2006, pp. 615-625.
Elsevier DOI
0606
BibRef
Earlier:
FaceVideo04(80).
IEEE DOI
0502
Facial action coding; Support vector machines; Adaboost
See also Towards an Optimal Affect-Sensitive Instructional System of cognitive skills.
BibRef
Bartlett, M.S.[Marian Stewart],
Littlewort, G.C.[Gwen C.],
Frank, M.[Mark],
Lainscsek, C.[Claudia],
Fasel, I.R.[Ian R.],
Movellan, J.R.[Javier R.],
Fully Automatic Facial Action Recognition in Spontaneous Behavior,
FGR06(223-230).
IEEE DOI
0604
BibRef
Earlier:
Recognizing Facial Expression: Machine Learning and Application to
Spontaneous Behavior,
CVPR05(II: 568-573).
IEEE DOI
0507
BibRef
Braathen, B.,
Bartlett, M.S.,
Littlewort, G.C.,
Smith, E.,
Movellan, J.R.,
An approach to automatic recognition of spontaneous facial actions,
AFGR02(345-350).
IEEE DOI
0206
BibRef
Whitehill, J.[Jacob],
Littlewort, G.C.[Gwen C.],
Fasel, I.R.[Ian R.],
Bartlett, M.S.[Marian S.],
Movellan, J.R.[Javier R.],
Toward Practical Smile Detection,
PAMI(31), No. 11, November 2009, pp. 2106-2111.
IEEE DOI
0910
Explore whether learning can be applied to a practical scenario.
Includes a dataset of thousands of different people.
BibRef
Wu, T.F.[Ting-Fan],
Butko, N.J.[Nicholas J.],
Ruvolo, P.[Paul],
Whitehill, J.[Jacob],
Bartlett, M.S.[Marian S.],
Movellan, J.R.[Javier R.],
Multilayer Architectures for Facial Action Unit Recognition,
SMC-B(42), No. 4, August 2012, pp. 1027-1038.
IEEE DOI
1208
BibRef
Earlier:
Action unit recognition transfer across datasets,
FG11(889-896).
IEEE DOI
1103
BibRef
Park, S.S.[Sung-Soo],
Kim, D.J.[Dai-Jin],
Subtle facial expression recognition using motion magnification,
PRL(30), No. 7, 1 May 2009, pp. 708-716.
Elsevier DOI
0904
BibRef
Earlier:
Spontaneous facial expression classification with facial motion vectors,
FG08(1-6).
IEEE DOI
0809
Subtle facial expression recognition; Motion magnification; Motion
estimation; Feature point tracking; Active appearance models
BibRef
Park, S.S.[Sung-Soo],
Shin, J.J.[Jong-Ju],
Kim, D.J.[Dai-Jin],
Facial expression analysis with facial expression deformation,
ICPR08(1-4).
IEEE DOI
0812
BibRef
Pfister, T.[Tomas],
Pietikäinen, M.[Matti],
Automatic identification of facial clues to lies,
SPIE(Newsroom), January 4, 2012.
DOI Link
1201
Computers can now detect micro-expressions that reveal emotions people
try to conceal.
BibRef
Pfister, T.[Tomas],
Li, X.B.[Xiao-Bai],
Zhao, G.Y.[Guo-Ying],
Pietikainen, M.[Matti],
Recognising spontaneous facial micro-expressions,
ICCV11(1449-1456).
IEEE DOI
PDF File. Video of talk:
WWW Link.
1201
BibRef
And:
Differentiating spontaneous from posed facial expressions within a
generic facial expression recognition framework,
SISM11(868-875).
IEEE DOI
1201
BibRef
Zhu, Y.F.[Yun-Feng],
de la Torre, F.[Fernando],
Cohn, J.F.[Jeffery F.],
Zhang, Y.J.[Yu-Jin],
Dynamic Cascades with Bidirectional Bootstrapping for Action Unit
Detection in Spontaneous Facial Behavior,
AffCom(2), No. 2, 2011, pp. 79-91.
IEEE DOI
1202
BibRef
Ding, X.Y.[Xiao-Yu],
Chu, W.S.[Wen-Sheng],
de la Torre, F.[Fernando],
Cohn, J.F.[Jeffery F.],
Wang, Q.[Qiao],
Cascade of Tasks for facial expression analysis,
IVC(51), No. 1, 2016, pp. 36-48.
Elsevier DOI
1606
BibRef
Earlier:
Facial Action Unit Event Detection by Cascade of Tasks,
ICCV13(2400-2407)
IEEE DOI
1403
Automated facial expression analysis
BibRef
Wan, S.H.[Shao-Hua],
Aggarwal, J.K.,
Spontaneous facial expression recognition:
A robust metric learning approach,
PR(47), No. 5, 2014, pp. 1859-1868.
Elsevier DOI
1402
BibRef
Earlier:
A scalable metric learning-based voting method for expression
recognition,
FG13(1-8)
IEEE DOI
1309
Spontaneous facial expression recognition
Gabor filters
BibRef
Abd El Meguid, M.K.,
Levine, M.D.,
Fully automated recognition of spontaneous facial expressions in
videos using random forest classifiers,
AffCom(5), No. 2, April 2014, pp. 141-154.
IEEE DOI
1411
decision trees
BibRef
Wang, S.F.[Shang-Fei],
Wu, C.L.[Chong-Liang],
He, M.H.[Meng-Hua],
Wang, J.[Jun],
Ji, Q.A.[Qi-Ang],
Posed and spontaneous expression recognition through modeling their
spatial patterns,
MVA(26), No. 2-3, April 2015, pp. 219-231.
Springer DOI
1504
BibRef
Wang, S.F.[Shang-Fei],
Wu, C.L.[Chong-Liang],
Ji, Q.A.[Qi-Ang],
Capturing global spatial patterns for distinguishing posed and
spontaneous expressions,
CVIU(147), No. 1, 2016, pp. 69-76.
Elsevier DOI
1605
Global spatial patterns
BibRef
Wu, C.L.[Chong-Liang],
Wang, S.F.[Shang-Fei],
Posed and Spontaneous Expression Recognition Through Restricted
Boltzmann Machine,
MMMod16(I: 127-137).
Springer DOI
1601
BibRef
Wu, S.[Shan],
Wang, S.F.[Shang-Fei],
Wang, J.[Jun],
Enhanced facial expression recognition by age,
FG15(1-6)
IEEE DOI
1508
belief networks
BibRef
Liu, Z.L.[Zhi-Lei],
Wang, S.F.[Shang-Fei],
Posed and spontaneous expression distinguishment from infrared thermal
images,
ICPR12(1108-1111).
WWW Link.
1302
BibRef
Bousmalis, K.[Konstantinos],
Mehu, M.[Marc],
Pantic, M.[Maja],
Towards the automatic detection of spontaneous agreement and
disagreement based on nonverbal behaviour: A survey of related cues,
databases, and tools,
IVC(31), No. 2, February 2013, pp. 203-221.
Elsevier DOI
1303
Agreement; Disagreement; Nonverbal behaviour; Social signal processing
BibRef
Bousmalis, K.[Konstantinos],
Morency, L.P.[Louis-Philippe],
Pantic, M.[Maja],
Modeling hidden dynamics of multimodal cues for spontaneous agreement
and disagreement recognition,
FG11(746-752).
IEEE DOI
1103
BibRef
Liu, M.Y.[Meng-Yi],
Wang, R.P.[Rui-Ping],
Shan, S.G.[Shi-Guang],
Chen, X.L.[Xi-Lin],
Learning prototypes and similes on Grassmann manifold for spontaneous
expression recognition,
CVIU(147), No. 1, 2016, pp. 95-101.
Elsevier DOI
1605
Expression prototype
BibRef
Liu, M.Y.[Meng-Yi],
Shan, S.G.[Shi-Guang],
Wang, R.P.[Rui-Ping],
Chen, X.L.[Xi-Lin],
Learning Expressionlets via Universal Manifold Model for Dynamic
Facial Expression Recognition,
IP(25), No. 12, December 2016, pp. 5920-5932.
IEEE DOI
1612
emotion recognition
BibRef
Liu, M.Y.[Meng-Yi],
Li, S.X.[Shao-Xin],
Shan, S.G.[Shi-Guang],
Wang, R.P.[Rui-Ping],
Chen, X.L.[Xi-Lin],
Deeply Learning Deformable Facial Action Parts Model for Dynamic
Expression Analysis,
ACCV14(IV: 143-157).
Springer DOI
1504
BibRef
Earlier: A1, A3, A4, A5, Only:
Learning Expressionlets on Spatio-temporal Manifold for Dynamic
Facial Expression Recognition,
CVPR14(1749-1756)
IEEE DOI
1409
BibRef
Liong, S.T.[Sze-Teng],
See, J.[John],
Phan, R.C.W.[Raphael C.W.],
Oh, Y.H.[Yee-Hui],
Ngo, A.C.L.[Anh Cat Le],
Wong, K.[Kok_Sheik],
Tan, S.W.[Su-Wei],
Spontaneous subtle expression detection and recognition based on
facial strain,
SP:IC(47), No. 1, 2016, pp. 170-182.
Elsevier DOI
1610
Subtle expressions
BibRef
Li, Y.Q.[Yong-Qiang],
Mavadati, S.M.[S. Mohammad],
Mahoor, M.H.[Mohammad H.],
Zhao, Y.P.[Yong-Ping],
Ji, Q.A.[Qi-Ang],
Measuring the intensity of spontaneous facial action units with
dynamic Bayesian network,
PR(48), No. 11, 2015, pp. 3417-3427.
Elsevier DOI
1506
BibRef
Earlier: A1, A3, A3, A5, Only:
A unified probabilistic framework for measuring the intensity of
spontaneous facial action units,
FG13(1-7)
IEEE DOI
1309
Spontaneous facial expression
Bayes methods
BibRef
Zhang, X.[Xiao],
Mahoor, M.H.[Mohammad H.],
Task-dependent multi-task multiple kernel learning for facial action
unit detection,
PR(51), No. 1, 2016, pp. 187-196.
Elsevier DOI
1601
Facial action unit detection
BibRef
Zhang, X.[Xiao],
Mahoor, M.H.,
Nielsen, R.D.,
On multi-task learning for facial action unit detection,
IVCNZ13(202-207)
IEEE DOI
1402
face recognition
BibRef
Zhang, X.[Xiao],
Mahoor, M.H.[Mohammad H.],
Mavadati, S.M.[S. Mohammad],
Cohn, J.F.[Jeffrey F.],
A lp-norm MTMKL framework for simultaneous detection of multiple
facial action units,
WACV14(1104-1111)
IEEE DOI
1406
Databases
BibRef
Mohammadi, M.R.,
Fatemizadeh, E.,
Mahoor, M.H.,
An Adaptive Bayesian Source Separation Method for Intensity
Estimation of Facial AUs,
AffCom(10), No. 2, April 2019, pp. 144-154.
IEEE DOI
1906
Gold, Estimation, Source separation, Bayes methods, Databases,
Encoding, Linear regression, Bayesian method, facial action units,
sparse regression
BibRef
Khorrami, P.,
Paine, T.L.,
Huang, T.S.,
Do Deep Neural Networks Learn Facial Action Units When Doing
Expression Recognition?,
CV4AC15(19-27)
IEEE DOI
1602
Benchmark testing
BibRef
Mohammadi, M.R.,
Fatemizadeh, E.,
Mahoor, M.H.,
Intensity Estimation of Spontaneous Facial Action Units Based on
Their Sparsity Properties,
Cyber(46), No. 3, March 2016, pp. 817-826.
IEEE DOI
1602
Atomic measurements
BibRef
Liu, Y.J.,
Zhang, J.K.,
Yan, W.J.,
Wang, S.J.,
Zhao, G.,
Fu, X.,
A Main Directional Mean Optical Flow Feature for Spontaneous
Micro-Expression Recognition,
AffCom(7), No. 4, October 2016, pp. 299-310.
IEEE DOI
1612
Adaptive optics
BibRef
Huang, M.X.,
Ngai, G.,
Hua, K.A.,
Chan, S.C.F.,
Leong, H.V.,
Identifying User-Specific Facial Affects from Spontaneous Expressions
with Minimal Annotation,
AffCom(7), No. 4, October 2016, pp. 360-373.
IEEE DOI
1612
Data models
BibRef
Ngo, A.C.L.[A. C. Le],
See, J.,
Phan, R.C.W.[Raphael Chung-Wei],
Sparsity in Dynamics of Spontaneous Subtle Emotions:
Analysis and Application,
AffCom(8), No. 3, July 2017, pp. 396-411.
IEEE DOI
1709
Databases, Dynamics, Emotion recognition, Face recognition,
Feature extraction, Image reconstruction, Visualization,
Micro-expression recognition, Spontaneous subtle emotions,
data sparsity, dynamic mode decomposition, emotion, suppression
BibRef
Perusquía-Hernández, M.,
Hirokawa, M.,
Suzuki, K.,
A Wearable Device for Fast and Subtle Spontaneous Smile Recognition,
AffCom(8), No. 4, October 2017, pp. 522-533.
IEEE DOI
1712
Electrodes, Electromyography, Emotion recognition, Face,
Face recognition, Robustness, Tools, Electromyography,
wearable interface
BibRef
Davison, A.K.,
Lansley, C.,
Costen, N.,
Tan, K.,
Yap, M.H.,
SAMM: A Spontaneous Micro-Facial Movement Dataset,
AffCom(9), No. 1, January 2018, pp. 116-129.
IEEE DOI
1804
emotion recognition, face recognition, image motion analysis,
learning (artificial intelligence),
micro-expressions
BibRef
Alashkar, T.,
Amor, B.B.,
Daoudi, M.,
Berretti, S.,
Spontaneous Expression Detection from 3D Dynamic Sequences by
Analyzing Trajectories on Grassmann Manifolds,
AffCom(9), No. 2, April 2018, pp. 271-284.
IEEE DOI
1806
Databases, Face, Manifolds, Pain,
Videos, Depth sequences,
spontaneous expression
BibRef
Perveen, N.[Nazil],
Roy, D.[Debaditya],
Mohan, C.K.[Chalavadi Krishna],
Spontaneous Expression Recognition Using Universal Attribute Model,
IP(27), No. 11, November 2018, pp. 5575-5584.
IEEE DOI
1809
emotion recognition, face recognition, feature extraction,
Gaussian processes, image classification, image motion analysis,
Gaussian mixture model
BibRef
Qu, F.,
Wang, S.,
Yan, W.,
Li, H.,
Wu, S.,
Fu, X.,
CAS(ME)^2: A Database for Spontaneous Macro-Expression and
Micro-Expression Spotting and Recognition,
AffCom(9), No. 4, October 2018, pp. 424-436.
IEEE DOI
1812
Databases, Videos, Face recognition, Psychology, Encoding, Labeling,
Macro-expression and micro-expression spotting,
facial action coding system
BibRef
Li, X.,
Hong, X.,
Moilanen, A.,
Huang, X.,
Pfister, T.,
Zhao, G.,
Pietikäinen, M.,
Towards Reading Hidden Emotions: A Comparative Study of Spontaneous
Micro-Expression Spotting and Recognition Methods,
AffCom(9), No. 4, October 2018, pp. 563-577.
IEEE DOI
1812
Videos, Cameras, Training, Face recognition, Emotion recognition,
Micro-expression, facial expression recognition,
HOG
BibRef
Dapogny, A.[Arnaud],
Bailly, K.[Kevin],
Dubuisson, S.[Séverine],
Confidence-Weighted Local Expression Predictions for Occlusion Handling
in Expression Recognition and Action Unit Detection,
IJCV(126), No. 2-4, April 2018, pp. 255-271.
Springer DOI
1804
BibRef
Earlier:
Multi-Output Random Forests for Facial Action Unit Detection,
FG17(135-140)
IEEE DOI
1707
BibRef
Earlier:
Pairwise Conditional Random Forests for Facial Expression Recognition,
ICCV15(3783-3791)
IEEE DOI
1602
BibRef
And:
Dynamic facial expression recognition by joint static and multi-time
gap transition classification,
FG15(1-6)
IEEE DOI
1508
Face, Feature extraction, Gold, Machine learning, Radio frequency,
Training, Vegetation
BibRef
Dapogny, A.[Arnaud],
Bailly, K.[Kevin],
Dubuisson, S.[Séverine],
Dynamic Pose-Robust Facial Expression Recognition by Multi-View
Pairwise Conditional Random Forests,
AffCom(10), No. 2, April 2019, pp. 167-181.
IEEE DOI
1906
Face, Videos, Training, Vegetation,
Testing, Spontaneous facial expression recognition, dynamics,
real-time
BibRef
Dapogny, A.[Arnaud],
Bailly, K.[Kevin],
Investigating Deep Neural Forests for Facial Expression Recognition,
FG18(629-633)
IEEE DOI
1806
Face, Forestry, Noise measurement, Radio frequency, Runtime, Training,
Vegetation, Deep learning, Deep neural forests,
Random Forests
BibRef
Khan, R.A.[Rizwan Ahmed],
Crenn, A.[Arthur],
Meyer, A.[Alexandre],
Bouakaz, S.[Saida],
A novel database of children's spontaneous facial expressions
(LIRIS-CSE),
IVC(83-84), 2019, pp. 61-69.
Elsevier DOI
1904
See also Children Spontaneous Facial Expression Video Database (LIRIS-CSE). Facial expressions database, Spontaneous expressions,
Convolutional neural network, Expression recognition, Transfer learning
BibRef
Bian, C.L.[Cun-Ling],
Zhang, Y.[Ya],
Yang, F.[Fei],
Bi, W.[Wei],
Lu, W.G.[Wei-Gang],
Spontaneous facial expression database for academic emotion inference
in online learning,
IET-CV(13), No. 3, April 2019, pp. 329-337.
DOI Link
1904
BibRef
Xia, Z.,
Hong, X.,
Gao, X.,
Feng, X.,
Zhao, G.,
Spatiotemporal Recurrent Convolutional Networks for Recognizing
Spontaneous Micro-Expressions,
MultMed(22), No. 3, March 2020, pp. 626-640.
IEEE DOI
2003
BibRef
And:
Corrections:
MultMed(22), No. 4, April 2020, pp. 1111-1111.
IEEE DOI
2004
Spatiotemporal phenomena, Feature extraction, Task analysis,
Videos, Training, Strain, Deep learning, Balanced Loss
BibRef
Zhu, X.L.[Xiao-Liang],
Chen, Z.J.[Zi-Jian],
Dual-modality spatiotemporal feature learning for spontaneous facial
expression recognition in e-learning using hybrid deep neural network,
VC(36), No. 4, April 2020, pp. 743-755.
WWW Link.
2004
BibRef
Qayyum, A.[Abdul],
Razzak, I.[Imran],
Moustafa, N.[Nour],
Mazher, M.[Moona],
Progressive ShallowNet for large scale dynamic and spontaneous facial
behaviour analysis in children,
IVC(119), 2022, pp. 104375.
Elsevier DOI
2202
Psychological health, Human computer interaction, Emotion care,
Depressed, Facial behavior recognition, Patient monitoring
BibRef
Li, J.T.[Jing-Ting],
Dong, Z.Z.[Zi-Zhao],
Lu, S.Y.[Shao-Yuan],
Wang, S.J.[Su-Jing],
Yan, W.J.[Wen-Jing],
Ma, Y.[Yinhuan],
Liu, Y.[Ye],
Huang, C.[Changbing],
Fu, X.L.[Xiao-Lan],
CAS(ME)3: A Third Generation Facial Spontaneous Micro-Expression
Database With Depth Information and High Ecological Validity,
PAMI(45), No. 3, March 2023, pp. 2782-2800.
IEEE DOI
2302
Databases, Psychology, Face recognition, Videos, Iron,
Emotion recognition, Trajectory, Micro-expression, multi-modality
BibRef
Li, X.B.[Xiao-Bai],
Cheng, S.[Shiyang],
Li, Y.[Yante],
Behzad, M.[Muzammil],
Shen, J.[Jie],
Zafeiriou, S.[Stefanos],
Pantic, M.[Maja],
Zhao, G.Y.[Guo-Ying],
4DME: A Spontaneous 4D Micro-Expression Dataset With Multimodalities,
AffCom(14), No. 4, October 2023, pp. 3031-3047.
IEEE DOI
2312
BibRef
Ulrich, L.[Luca],
Marcolin, F.[Federica],
Vezzetti, E.[Enrico],
Nonis, F.[Francesca],
Mograbi, D.C.[Daniel C.],
Scurati, G.W.[Giulia Wally],
Dozio, N.[Nicolò],
Ferrise, F.[Francesco],
CalD3r and MenD3s: Spontaneous 3D facial expression databases,
JVCIR(98), 2024, pp. 104033.
Elsevier DOI
2402
3D facial expression, Spontaneous expressions,
Facial expression recognition, Ecological validity, Human-computer interaction
BibRef
Healey, J.,
Wang, H.,
Chhaya, N.,
Challenges in Recognizing Spontaneous and Intentionally Expressed
Reactions to Positive and Negative Images,
EmotioNet20(1622-1630)
IEEE DOI
2008
Emotion recognition, Face recognition, Encoding,
Image recognition
BibRef
Yang, Y.[Yan],
Hossain, M.Z.[Md Zakir],
Gedeon, T.[Tom],
Rahman, S.[Shafin],
Realsmilenet: A Deep End-to-end Network for Spontaneous and Posed Smile
Recognition,
ACCV20(V:21-37).
Springer DOI
2103
BibRef
Fabiano, D.,
Canavan, S.,
Spontaneous and Non-Spontaneous 3D Facial Expression Recognition
Using a Statistical Model with Global and Local Constraints,
ICIP18(3089-3093)
IEEE DOI
1809
Shape, Face, Face recognition, Databases,
Solid modeling, Computational modeling, Expression, classification,
non-spontaneous
BibRef
Han, Y.,
Li, B.,
Lai, Y.,
Liu, Y.,
CFD: A Collaborative Feature Difference Method for Spontaneous
Micro-Expression Spotting,
ICIP18(1942-1946)
IEEE DOI
1809
Feature extraction, Collaboration, Video sequences, Histograms,
Optical imaging, Face, Indexes, Micro-expression, spotting features,
weighted ROIs
BibRef
Hadar, D.,
Tron, T.,
Weinshall, D.,
Implicit Media Tagging and Affect Prediction from RGB-D Video of
Spontaneous Facial Expressions,
FG17(727-734)
IEEE DOI
1707
Cameras, Correlation, Databases, Media, Predictive models, Reliability, Tagging
BibRef
Girard, J.M.,
Chu, W.S.,
Jeni, L.A.,
Cohn, J.F.,
Sayette Group Formation Task (GFT) Spontaneous Facial Expression
Database,
FG17(581-588)
IEEE DOI
1707
Alcoholic beverages, Cameras, Context, Databases, Encoding, Gold, Reliability
BibRef
Shibasaki, Y.[Yasuhiro],
Funakoshi, K.[Kotaro],
Shinoda, K.[Koichi],
Boredom Recognition Based on Users' Spontaneous Behaviors in Multiparty
Human-Robot Interactions,
MMMod17(I: 677-689).
Springer DOI
1701
BibRef
Mandal, B.[Bappaditya],
Lee, D.[David],
Ouarti, N.[Nizar],
Distinguishing Posed and Spontaneous Smiles by Facial Dynamics,
SFBA16(I: 552-566).
Springer DOI
1704
BibRef
Shreve, M.,
Bernal, E.A.,
Li, Q.,
Kumar, J.,
Bala, R.,
A study on the discriminability of faces from spontaneous facial
expressions,
ICIP16(1674-1678)
IEEE DOI
1610
Feature extraction
BibRef
Zaker, N.,
Mahoor, M.H.,
Messinger, D.S.,
Cohn, J.F.,
Jointly detecting infants' multiple facial action units expressed
during spontaneous face-to-face communication,
ICIP14(1357-1360)
IEEE DOI
1502
Equations
BibRef
Liu, P.[Peng],
Yin, L.J.[Li-Jun],
Spontaneous facial expression analysis based on temperature changes
and head motions,
FG15(1-6)
IEEE DOI
1508
emotion recognition
BibRef
Reale, M.[Michael],
Liu, P.[Peng],
Yin, L.J.[Li-Jun],
Using eye gaze, head pose, and facial expression for personalized
non-player character interaction,
CVCG11(13-18).
IEEE DOI
1106
BibRef
Sun, Y.[Yi],
Reale, M.[Michael],
Yin, L.J.[Li-Jun],
Recognizing partial facial action units based on 3D dynamic range data
for facial expression recognition,
FG08(1-8).
IEEE DOI
0809
BibRef
Tong, Y.[Yan],
Chen, J.X.[Ji-Xu],
Ji, Q.A.[Qi-Ang],
Modeling and exploiting the spatio-temporal facial action dependencies
for robust spontaneous facial expression recognition,
CVPR4HB09(34-41).
IEEE DOI
0906
BibRef
Ngo, A.C.L.[Anh Cat Le],
Phan, R.C.W.[Raphael Chung-Wei],
See, J.[John],
Spontaneous Subtle Expression Recognition:
Imbalanced Databases and Solutions,
ACCV14(IV: 33-48).
Springer DOI
1504
BibRef
Yan, W.J.[Wen-Jing],
Wu, Q.[Qi],
Liu, Y.J.[Yong-Jin],
Wang, S.J.[Su-Jing],
Fu, X.L.[Xiao-Lan],
CASME database: A dataset of spontaneous micro-expressions collected
from neutralized faces,
FG13(1-7)
IEEE DOI
1309
Dataset, Facial Expressions. computer vision
BibRef
Li, X.B.[Xiao-Bai],
Pfister, T.,
Huang, X.H.[Xiao-Hua],
Zhao, G.Y.[Guo-Ying],
Pietikainen, M.[Matti],
A Spontaneous Micro-expression Database:
Inducement, collection and baseline,
FG13(1-6)
IEEE DOI
1309
computer vision
BibRef
Kodra, E.,
Senechal, T.,
McDuff, D.J.,
El Kaliouby, R.,
From dials to facial coding: Automated detection of spontaneous
facial expressions for media research,
FG13(1-6)
IEEE DOI
1309
face recognition
BibRef
Reilly Delannoy, J.[Jane],
McDonald, J.B.[John B.],
Estimation of the Temporal Dynamics of Posed and Spontaneous Facial
Expression Formation Using LLE,
IMVIP09(139-144).
IEEE DOI
0909
BibRef
Earlier:
Automatic estimation of the dynamics of facial expression using a
three-level model of intensity,
FG08(1-6).
IEEE DOI
0809
BibRef
Zeng, Z.H.[Zhi-Hong],
Fu, Y.[Yun],
Roisman, G.I.,
Wen, Z.[Zhen],
Hu, Y.X.[Yu-Xiao],
Huang, T.S.,
One-Class Classification for Spontaneous Facial Expression Analysis,
FGR06(281-286).
IEEE DOI
0604
BibRef
Chapter on Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics continues in
Facial Feature Tracking for Expressions .