21.3.6.1.8 Face Action Units for Expressions and Motion Analysis, FAU, FACS

Chapter Contents (Back)
Face Recognition. Facial Expressions. Application, Faces. Faces, Expression. Facial Action Units. FACS. FAU. FAU, FACS

Huang, C.L., Huang, Y.M.,
Facial Expression Recognition Using Model-Based Feature Extraction and Action Parameter(s) Classification,
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Essa, I.A.[Irfan A.], and Pentland, A.P.[Alex P.],
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PAMI(19), No. 7, July 1997, pp. 757-763.
IEEE DOI 9708
BibRef
Earlier:
Facial Expression Recognition Using Image Motion,
MBR97(Chapter 12). MIT. BibRef
Earlier:
Facial Expression Recognition Using a Dynamic Model and Motion Energy,
ICCV95(360-367).
IEEE DOI BibRef
And: Vismod-307, 1995.
HTML Version. and
PS File. Spatio-temporal technique for expression recognition. Rather than use the heuristic (psychological system) FACS, use a probabilistic scheme to characterize motion and muscle activation. BibRef

Essa, I.A., Pentland, A.P.,
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PS File. BibRef

Essa, I.A.[Irfan A.], Darrell, T.J.[Trevor J.], Pentland, A.P.[Alex P.],
Tracking Facial Motion,
Vismod-272, 1994.
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PS File. BibRef 9400

Essa, I.A.[Irfan A.],
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Zhang, L.[Liang],
Automatic Adaptation of a Face Model Using Action Units for Semantic Coding of Videophone Sequences,
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Donato, G.[Gianluca], Bartlett, M.S.[Marian Stewart], Hager, J.C.[Joseph C.], Ekman, P.[Paul], Sejnowski, T.J.[Terrence J.],
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PAMI(21), No. 10, October 1999, pp. 974-989.
IEEE DOI Uses the FACS ( See also Facial Action Coding System: A Technique for the Measurement of Facial Movement, The. ) coding system. 96% for 12 facial actions. BibRef 9910

Bartlett, M.S., Hager, J.C., Ekman, P., Sejnowski, T.J.,
Measuring Facial Expressions by Computer Image Analysis,
Psychophysiology(36), 1999, pp. 253-264. BibRef 9900

Fleet, D.J.[David J.], Black, M.J.[Michael J.], Yacoob, Y.[Yaser], Jepson, A.D.[Allan D.],
Design and Use of Linear Models for Image Motion Analysis,
IJCV(36), No. 3, February-March 2000, pp. 171-193.
DOI Link 0003

PDF File. See also Probabilistic Detection and Tracking of Motion Boundaries. See also Recognizing Facial Expressions in Image Sequences Using Local Parameterized Models of Image Motion. See also Estimating Optical-Flow in Segmented Images Using Variable-Order Parametric Models with Local Deformations. BibRef

Black, M.J.[Michael J.],
Explaining Optical Flow Events with Parameterized Spatio-temporal Models,
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IEEE DOI Generative Spatio-Temporal model. Basis for flow fields. Used for facial expressions. BibRef 9900

Black, M.J., Yacoob, Y., Jepson, A.D., Fleet, D.J.,
Learning Parameterized Models of Image Motion,
CVPR97(561-567).
IEEE DOI 9704
Several applications. BibRef

Tian, Y.L.[Ying-Li], Kanade, T.[Takeo], Cohn, J.F.[Jeffrey F.],
Recognizing Action Units for Facial Expression Analysis,
PAMI(23), No. 2, February 2001, pp. 97-115.
IEEE DOI 0102
BibRef
And: CMU-RI-TR-99-40, December, 1999.
HTML Version. BibRef
And:
Recognizing Upper Face Action Units for Facial Expression Analysis,
CVPR00(I: 294-301).
IEEE DOI 0005
Analyze expressions using permanent facial features and transient features. Describe expressions in terms of action units rather than prototypical expressions. Compares results with: See also Measuring Facial Expressions by Computer Image Analysis. See also Classifying Facial Actions. See also Automated Face Analysis by Feature Point Tracking Has High Concurrent Validity with Manual FACS Coding. and See also Detection, Tracking, and Classification of Action Units in Facial Expression. BibRef

Tian, Y.L., Kanade, T., Cohn, J.F.,
Recognizing Facial Actions by Combining Geometric Features and Regional Appearance Patterns,
CMU-RI-TR-01-01, January 2001.
PDF File. 0102
BibRef

Tian, Y.L.[Ying-Li], Kanade, T.[Takeo], Cohn, J.F.[Jeffrey F.],
Evaluation of gabor-wavelet-based facial action unit recognition in image sequences of increasing complexity,
AFGR02(218-223).
IEEE DOI 0206
BibRef
Earlier:
Recognizing Lower Face Action Units in Facial Expression,
AFGR00(484-490).
IEEE DOI 0003
BibRef
And:
Multi-State Based Facial Feature Tracking and Detection,
CMU-RI-TR-99-18, August, 1999.
HTML Version. BibRef

Cohn, J.F.[Jeffrey F.], Kanade, T.[Takeo],
Use of automated facial image analysis for measurement of emotion expression,
EmotionElicitation06(xx-yy).
HTML Version. BibRef 0600

Cohn, J.F.[Jeffrey F.], Ambadar, Z., and Ekman, P.,
Observer-based measurement of facial expression with the Facial Action Coding System,
EmotionElicitation06(xx-yy).
HTML Version. BibRef 0600

Wang, T.H.[Te-Hsun], Lien, J.J.J.[Jenn-Jier James],
Facial expression recognition system based on rigid and non-rigid motion separation and 3D pose estimation,
PR(42), No. 5, May 2009, pp. 962-977.
Elsevier DOI 0902
Facial expression recognition; FACS action units; Rigid and non-rigid motion separation; 3D pose estimation; Perspective projection See also view-based statistical system for multi-view face detection and pose estimation, A. BibRef

Lai, T.H.[Tzung-Heng], Wang, T.H.[Te-Hsun], Lien, J.J.J.[Jenn-Jier James],
Incremental Perspective Motion Model for Rigid and Non-rigid Motion Separation,
PSIVT07(613-624).
Springer DOI 0712
Motion extraction in facial expression analysis. BibRef

Lien, J.J.J.[James J.J.], Kanade, T.[Takeo], Cohn, J.F.[Jeffrey F.], Li, C.C.[Ching-Chung],
Automated Facial Expression Recognition Based on FACS Action Units,
AFGR98(390-395).
IEEE DOI BibRef 9800

Lien, J.J.J.,
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CMU-RI-TR-98-31, April, 1998.
HTML Version. BibRef 9804

Lien, J.J.J.[James J.J.], Kanade, T.[Takeo], Cohn, J.F.[Jeffrey F.], Li, C.C.[Ching-Chung], Zlochower, A.J.[Adena J.],
Subtly Different Facial Expression Recognition and Expression Intensity Estimation,
CVPR98(853-859).
IEEE DOI
PDF File. BibRef 9800

Cohn, J.F., Zlochower, A.J., Lien, J.J.J., Kanade, T.,
Automated Face Analysis by Feature Point Tracking Has High Concurrent Validity with Manual FACS Coding,
Psychophysiology(36), 1999, pp. 35-43.
PDF File. BibRef 9900
Earlier:
Feature-Point Tracking by Optical Flow Discriminates Subtle Differences in Facial Expression,
AFGR98(396-401).
IEEE DOI BibRef

CMU Facial Expression Database ,
1999 Dataset, Faces. Dataset, Facial Expression.
HTML Version. Includes annotation.

Lien, J.J.J.[James J.J.], Kanade, T.[Takeo], Cohn, J.F.[Jeffrey F.], Li, C.C.[Ching-Chung],
Detection, Tracking, and Classification of Action Units in Facial Expression,
RAS(31), 2000, pp. 131-146. BibRef 0001

Tao, H.[Hai], Huang, T.S.[Thomas S.],
Visual Estimation and Compression of Facial Motion Parameters: Elements of a 3D Model-Based Video Coding System,
IJCV(50), No. 2, November 2002, pp. 111-125.
DOI Link 0210
BibRef
Earlier:
Explanation-based Facial Motion Tracking Using a Piecewise Bezier Volume Deformation Model,
CVPR99(I: 611-617).
IEEE DOI BibRef

Tao, H.[Hai], Huang, T.S.[Thomas S.],
A Piecewise Bézier Volume Deformation Model and Its Applications in Facial Motion Capture,
AIPU02(39-56). 0905
BibRef

Tao, H.[Hai], Lopez, R., Huang, T.S.,
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AFGR98(166-170).
IEEE DOI BibRef 9800

Pardŕs, M.[Montse], Bonafonte, A.[Antonio],
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SP:IC(17), No. 9, October 2002, pp. 675-688.
Elsevier DOI 0211
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Chuang, C.F.[Chao-Fa], Shih, F.Y.[Frank Y.],
Recognizing facial action units using independent component analysis and support vector machine,
PR(39), No. 9, September 2006, pp. 1795-1798.
Elsevier DOI 0606
Action unit; Independent component analysis; Support vector machine BibRef

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

Tong, Y.[Yan], Liao, W.H.[Wen-Hui], Ji, Q.A.[Qi-Ang],
Facial Action Unit Recognition by Exploiting Their Dynamic and Semantic Relationships,
PAMI(29), No. 10, October 2007, pp. 1683-1699.
IEEE DOI 0710
Integrate relations, dynamics, and appearance. See also Robust facial feature tracking under varying face pose and facial expression. BibRef

Wang, S.F.[Shang-Fei], Yang, J.J.[Jia-Jia], Gao, Z.[Zhen], Ji, Q.A.[Qi-Ang],
Feature and label relation modeling for multiple-facial action unit classification and intensity estimation,
PR(65), No. 1, 2017, pp. 71-81.
Elsevier DOI 1702
AU recognition BibRef

Zhu, Y.[Yachen], Wang, S.F.[Shang-Fei], Yue, L.H.[Li-Hua], Ji, Q.A.[Qi-Ang],
Multiple-Facial Action Unit Recognition by Shared Feature Learning and Semantic Relation Modeling,
ICPR14(1663-1668)
IEEE DOI 1412
Accuracy BibRef

Yang, J.J.[Jia-Jia], Wu, S.[Shan], Wang, S.F.[Shang-Fei], Ji, Q.A.[Qi-Ang],
Multiple facial action unit recognition enhanced by facial expressions,
ICPR16(4089-4094)
IEEE DOI 1705
Databases, Face recognition, Gold, Mathematical model, Probabilistic logic, Semantics, Training BibRef

Wu, S.[Shan], Wang, S.F.[Shang-Fei], Ji, Q.A.[Qi-Ang],
Multiple Facial Action Unit recognition by learning joint features and label relations,
ICPR16(2246-2251)
IEEE DOI 1705
Bayes methods, Face recognition, Facial features, Gold, Inference algorithms, Kernel, Training BibRef

Wang, Z.H.[Zi-Heng], Li, Y.Q.[Yong-Qiang], Wang, S.F.[Shang-Fei], Ji, Q.A.[Qi-Ang],
Capturing Global Semantic Relationships for Facial Action Unit Recognition,
ICCV13(3304-3311)
IEEE DOI 1403
AU recognition; RBM; Spatiotemporal relationship BibRef

Tong, Y.[Yan], Liao, W.H.[Wen-Hui], Xue, Z.[Zheng], Ji, Q.A.[Qi-Ang],
A Unified Probabilistic Framework for Facial Activity Modeling and xoUnderstanding,
CVPR07(1-8).
IEEE DOI 0706
BibRef

Tong, Y.[Yan], Chen, J.X.[Ji-Xu], Ji, Q.A.[Qi-Ang],
A Unified Probabilistic Framework for Spontaneous Facial Action Modeling and Understanding,
PAMI(32), No. 2, February 2010, pp. 258-273.
IEEE DOI 1001
See also Efficient 3D Upper Body Tracking with Self-Occlusions. See also Robust facial feature tracking under varying face pose and facial expression. BibRef

Chen, J.X.[Ji-Xu], Ji, Q.A.[Qi-Ang],
A hierarchical framework for simultaneous facial activity tracking,
FG11(679-686).
IEEE DOI 1103
BibRef

Gu, H.S.[Hai-Song], Ji, Q.A.[Qi-Ang],
Facial event classification with task oriented dynamic Bayesian network,
CVPR04(II: 870-875).
IEEE DOI 0408
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And:
An automated face reader for fatigue detection,
AFGR04(111-116).
WWW Link. 0411
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Buciu, I.[Ioan], Pitas, I.[Ioannis],
NMF, LNMF, and DNMF modeling of neural receptive fields involved in human facial expression perception,
JVCIR(17), No. 5, October 2006, pp. 958-969.
Elsevier DOI 0711
BibRef
Earlier: Erratum: JVCIR(18), No. 1, February 2007, pp. 100.
Elsevier DOI 0711
BibRef
Earlier:
Application of non-negative and local non negative matrix factorization to facial expression recognition,
ICPR04(I: 288-291).
IEEE DOI 0409
Image representation; Receptive fields; Facial expressions BibRef

Nikitidis, S.[Symeon], Tefas, A.[Anastasios], Nikolaidis, N.[Nikos], Pitas, I.[Ioannis],
Subclass discriminant Nonnegative Matrix Factorization for facial image analysis,
PR(45), No. 12, December 2012, pp. 4080-4091.
Elsevier DOI 1208
BibRef
Earlier:
Facial expression recognition using clustering discriminant Non-negative Matrix Factorization,
ICIP11(3001-3004).
IEEE DOI 1201
Nonnegative Matrix Factorization; Subclass discriminant analysis; Multiplicative updates; Facial expression recognition; Face recognition BibRef

Orfanidis, G.[Georgios], Tefas, A.[Anastasios], Nikolaidis, N.[Nikos], Pitas, I.[Ioannis],
Facial image clustering in stereoscopic videos using double spectral analysis,
SP:IC(33), No. 1, 2015, pp. 86-105.
Elsevier DOI 1504
Stereoscopic video BibRef

Nikitidis, S.[Symeon], Tefas, A.[Anastasios], Pitas, I.[Ioannis],
Maximum Margin Projection Subspace Learning for Visual Data Analysis,
IP(23), No. 10, October 2014, pp. 4413-4425.
IEEE DOI 1410
face recognition BibRef

Kotsia, I.[Irene], Pitas, I.[Ioannis],
Facial Expression Recognition in Image Sequences Using Geometric Deformation Features and Support Vector Machines,
IP(16), No. 1, January 2007, pp. 172-187.
IEEE DOI 0701
BibRef
Earlier:
Real Time Facial Expression Recognition from Image Sequences Using Support Vector Machines,
ICIP05(II: 966-969).
IEEE DOI 0512
BibRef

Kotsia, I.[Irene], Zafeiriou, S.P.[Stefanos P.], Pitas, I.[Ioannis],
Texture and shape information fusion for facial expression and facial action unit recognition,
PR(41), No. 3, March 2008, pp. 833-851.
Elsevier DOI 0711
BibRef
Earlier:
Fusion of Geometrical and Texture Information for Facial Expression Recognition,
ICIP06(2649-2652).
IEEE DOI 0610
Facial expression recognition; Facial Action Unit recognition; Discriminant Non-Negative Matrix Factorization; Multidimensional embedding; Support Vector Machines; Radial Basis Functions; Fusion BibRef

Kotsia, I.[Irene], Buciu, I.[Ioan], Pitas, I.[Ioannis],
An analysis of facial expression recognition under partial facial image occlusion,
IVC(26), No. 7, 2 July 2008, pp. 1052-1067.
Elsevier DOI 0804
Facial expression recognition; Gabor filters; Discriminant Non-negative Matrix Factorization; Support Vector Machines; Partial occlusion BibRef

Buciu, I.[Ioan], Kotropoulos, C.[Constantine], Pitas, I.[Ioannis],
Comparison of ICA approaches for facial expression recognition,
SIViP(3), No. 4, December 2009, pp. xx-yy.
Springer DOI 0911
BibRef
Earlier:
ICA and gabor representation for facial expression recognition,
ICIP03(II: 855-858).
IEEE DOI 0312
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Earlier:
On the stability of support vector machines for face detection,
ICIP02(III: 121-124).
IEEE DOI 0210
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Earlier:
Combining Support Vector Machines for Accurate Face Detection,
ICIP01(I: 1054-1057).
IEEE DOI 0108
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Kotsia, I.[Irene], Patras, I.[Ioannis],
Support tucker machines,
CVPR11(633-640).
IEEE DOI 1106
BibRef
Earlier:
Multiplicative Update Rules for Multilinear Support Tensor Machines,
ICPR10(33-36).
IEEE DOI 1008
See also Relative Margin Support Tensor Machines for gait and action recognition. BibRef

Kotsia, I.[Irene], Zafeiriou, S.P.[Stefanos P.], Nikolaidis, N.[Nikolaos], Pitas, I.[Ioannis],
Texture and Shape Information Fusion for Facial Action Unit Recognition,
ACHI08(77-82).
IEEE DOI 0802
BibRef

Bishay, M., Patras, I.,
Fusing Multilabel Deep Networks for Facial Action Unit Detection,
FG17(681-688)
IEEE DOI 1707
Correlation, Databases, Face, Feature extraction, Gold, Neurons, Training BibRef

Zafeiriou, S.P.[Stefanos P.], Petrou, M.[Maria],
Sparse representations for facial expressions recognition via L1 optimization,
CVCGI10(32-39).
IEEE DOI 1006
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Yang, P.[Peng], Liu, Q.S.[Qing-Shan], Metaxas, D.N.[Dimitris N.],
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PRL(30), No. 2, 15 January 2009, pp. 132-139.
Elsevier DOI 0804
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Earlier:
Similarity Features for Facial Event Analysis,
ECCV08(I: 685-696).
Springer DOI 0810
BibRef
Earlier:
Boosting Coded Dynamic Features for Facial Action Units and Facial Expression Recognition,
CVPR07(1-6).
IEEE DOI 0706
Pattern recognition; Facial expression; Video understanding; Boosting BibRef

Yang, P.[Peng], Liu, Q.S.[Qing-Shan], Metaxas, D.N.[Dimitris N.],
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CVIU(115), No. 3, March 2011, pp. 456-465.
Elsevier DOI 1103
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RankBoost with L1 regularization for facial expression recognition and intensity estimation,
ICCV09(1018-1025).
IEEE DOI 0909
Facial expression; Dynamic feature; Time resolution BibRef

Yang, P.[Peng], Liu, Q.S.[Qing-Shan], Metaxas, D.N.[Dimitris N.],
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CVPR10(2638-2644).
IEEE DOI 1006
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Yang, P.[Peng], Liu, Q.S.[Qing-Shan], Cui, X.Y.[Xin-Yi], Metaxas, D.N.[Dimitris N.],
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IEEE DOI 0806
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Koelstra, S.[Sander], Pantic, M.[Maja], Patras, I.[Ioannis],
A Dynamic Texture-Based Approach to Recognition of Facial Actions and Their Temporal Models,
PAMI(32), No. 11, November 2010, pp. 1940-1954.
IEEE DOI 1011
FAUs from texture. motion history images and nonrigid registration using free-form deformations. BibRef

Koelstra, S.[Sander], Pantic, M.[Maja],
Non-rigid registration using free-form deformations for recognition of facial actions and their temporal dynamics,
FG08(1-8).
IEEE DOI 0809
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Valstar, M.F.[Michel F.], Pantic, M.[Maja],
Fully Automatic Recognition of the Temporal Phases of Facial Actions,
SMC-B(42), No. 1, February 2012, pp. 28-43.
IEEE DOI 1201
BibRef
Earlier:
Combined Support Vector Machines and Hidden Markov Models for Modeling Facial Action Temporal Dynamics,
CVHCI07(118-127).
Springer DOI 0710
BibRef
Earlier:
Fully Automatic Facial Action Unit Detection and Temporal Analysis,
V4HCI06(149).
IEEE DOI 0609
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Sandbach, G.[Georgia], Zafeiriou, S.P.[Stefanos P.], Pantic, M.[Maja],
Local normal binary patterns for 3D facial action unit detection,
ICIP12(1813-1816).
IEEE DOI 1302
BibRef
Earlier:
Binary Pattern Analysis for 3D Facial Action Unit Detection,
BMVC12(119).
DOI Link 1301
BibRef

Martinez, B.[Brais], Valstar, M.F.[Michel F.], Binefa, X.[Xavier], Pantic, M.[Maja],
Local Evidence Aggregation for Regression-Based Facial Point Detection,
PAMI(35), No. 5, May 2013, pp. 1149-1163.
IEEE DOI 1304
BibRef
Earlier: A2, A1, A3, A4:
Facial point detection using boosted regression and graph models,
CVPR10(2729-2736).
IEEE DOI 1006
frontal and near-frontal. Use face shape to restrict feature point locations. BibRef

Martinez, B.[Brais], Valstar, M.F.[Michel F.],
L2,1-based regression and prediction accumulation across views for robust facial landmark detection,
IVC(47), No. 1, 2016, pp. 36-44.
Elsevier DOI 1605
Facial landmark detection BibRef

Sánchez-Lozano, E.[Enrique], Martinez, B.[Brais], Valstar, M.F.[Michel F.],
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PRL(73), No. 1, 2016, pp. 19-25.
Elsevier DOI 1604
Supervised descent method BibRef

Sánchez-Lozano, E.[Enrique], Martinez, B.[Brais], Tzimiropoulos, G.[Georgios], Valstar, M.F.[Michel F.],
Cascaded Continuous Regression for Real-Time Incremental Face Tracking,
ECCV16(VIII: 645-661).
Springer DOI 1611
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Valstar, M.F., Patras, I.[Ioannis], Pantic, M.[Maja],
Facial Action Unit Detection using Probabilistic Actively Learned Support Vector Machines on Tracked Facial Point Data,
VHCI05(III: 76-76).
IEEE DOI 0507
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Savran, A.[Arman], Sankur, B.[Bülent], Bilge, M.T.[M. Taha],
Comparative evaluation of 3D vs. 2D modality for automatic detection of facial action units,
PR(45), No. 2, February 2012, pp. 767-782.
Elsevier DOI 1110
BibRef
Earlier:
Facial action unit detection: 3D versus 2D modality,
CVPR4HB10(71-78).
IEEE DOI 1006
3D expression recognition; 3D facial expression database; Action unit detection; Facial action coding system; Modality fusion; Gabor wavelets BibRef

Savran, A.[Arman], Sankur, B.[Bulent], Bilge, M.T.[M. Taha],
Regression-based intensity estimation of facial action units,
IVC(30), No. 10, October 2012, pp. 774-784.
Elsevier DOI 1210
Action unit intensity estimation; 3D facial expression recognition; Facial Action Coding System; Feature selection; AdaBoost.RT; SVM regression BibRef

Savran, A.[Arman], Sankur, B.[Bulent],
Automatic detection of facial actions from 3D data,
HCI09(1993-2000).
IEEE DOI 0910
BibRef

Savran, A.[Arman], Sankur, B.[Bülent],
Non-rigid registration based model-free 3D facial expression recognition,
CVIU(162), No. 1, 2017, pp. 146-165.
Elsevier DOI 1710
Facial expression recognition 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

Polikovsky, S.[Senya], Kameda, Y.[Yoshinari], Ohta, Y.[Yuichi],
Facial Micro-Expression Detection in Hi-Speed Video Based on Facial Action Coding System (FACS),
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McDuff, D.J.[Daniel J.], el Kaliouby, R.[Rana], Picard, R.W.[Rosalind W.],
Crowdsourcing Facial Responses to Online Videos,
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IEEE DOI 1302
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McDuff, D.J.[Daniel J.], el Kaliouby, R.[Rana], Kassam, K.[Karim], Picard, R.W.[Rosalind W.],
Affect valence inference from facial action unit spectrograms,
AMFG10(17-24).
IEEE DOI 1006
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Senechal, T., McDuff, D.J.[Daniel J.], el Kaliouby, R.[Rana],
Facial Action Unit Detection Using Active Learning and an Efficient Non-linear Kernel Approximation,
CV4AC15(10-18)
IEEE DOI 1602
Approximation methods BibRef

McDuff, D.J.[Daniel J.], el Kaliouby, R.[Rana],
Applications of Automated Facial Coding in Media Measurement,
AffCom(8), No. 2, April 2017, pp. 148-160.
IEEE DOI 1706
Encoding, Face, Media, Motion pictures, TV, Testing, Webcams, Facial expressions, advertising, crowdsourcing, emotion, facial coding, marketing, media, measurement BibRef

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Linear subspaces for facial expression recognition,
SP:IC(29), No. 1, 2014, pp. 177-188.
Elsevier DOI 1402
Face analysis BibRef

Jiang, B.[Bihan], Valstar, M.F., Martinez, B., Pantic, M.,
A Dynamic Appearance Descriptor Approach to Facial Actions Temporal Modeling,
Cyber(44), No. 2, February 2014, pp. 161-174.
IEEE DOI 1403
Markov processes BibRef

Almaev, T.R., Martinez, B.[Brais], Valstar, M.F.[Michel F.],
Learning to Transfer: Transferring Latent Task Structures and Its Application to Person-Specific Facial Action Unit Detection,
ICCV15(3774-3782)
IEEE DOI 1602
Data models; Encoding; Face recognition; Facial muscles; Gold; Training BibRef

Mavadati, S.M.[S. Mohammad], Mahoor, M.H.[Mohammad H.],
Temporal Facial Expression Modeling for Automated Action Unit Intensity Measurement,
ICPR14(4648-4653)
IEEE DOI 1412
Accuracy BibRef

Mahoor, M.H.[Mohammad H.], Cadavid, S.[Steven], Messinger, D.S.[Daniel S.], Cohn, J.F.[Jeffrey F.],
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CVPR4HB09(74-80).
IEEE DOI 0906
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Wu, B.Y.[Bao-Yuan], Lyu, S.W.[Si-Wei], Hu, B.G.[Bao-Gang], Ji, Q.A.[Qi-Ang],
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PR(48), No. 7, 2015, pp. 2279-2289.
Elsevier DOI 1504
Multi-label learning BibRef

Li, Y.Q.[Yong-Qiang], Wu, B.Y.[Bao-Yuan], Ghanem, B.[Bernard], Zhao, Y.P.[Yong-Ping], Yao, H.X.[Hong-Xun], Ji, Q.A.[Qi-Ang],
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PR(60), No. 1, 2016, pp. 890-900.
Elsevier DOI 1609
Face action unit recognition BibRef

Wu, B.Y.[Bao-Yuan], Liu, Z.L.[Zhi-Lei], Wang, S.F.[Shang-Fei], Hu, B.G.[Bao-Gang], Ji, Q.A.[Qi-Ang],
Multi-label Learning with Missing Labels,
ICPR14(1964-1968)
IEEE DOI 1412
Conferences BibRef

Wu, B.Y.[Bao-Yuan], Lyu, S.W.[Si-Wei], Ghanem, B.[Bernard],
ML-MG: Multi-label Learning with Missing Labels Using a Mixed Graph,
ICCV15(4157-4165)
IEEE DOI 1602
multi-label learning with missing labels. Games; Horses; Image edge detection; Semantics; Training BibRef

Zhong, L.[Lin], Liu, Q.S.[Qing-Shan], Yang, P.[Peng], Huang, J.Z.[Jun-Zhou], Metaxas, D.N.[Dimitris N.],
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Cyber(45), No. 8, August 2015, pp. 1499-1510.
IEEE DOI 1506
Face recognition BibRef

Zhong, L.[Lin], Liu, Q.S.[Qing-Shan], Yang, P.[Peng], Liu, B.[Bo], Huang, J.Z.[Jun-Zhou], Metaxas, D.N.[Dimitris N.],
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CVPR12(2562-2569).
IEEE DOI 1208
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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],
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PR(48), No. 11, 2015, pp. 3417-3427.
Elsevier DOI 1506
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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.],
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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.,
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

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

Zhao, K.[Kaili], Chu, W.S.[Wen-Sheng], de la Torre, F.[Fernando], Cohn, J.F.[Jeffrey F.], Zhang, H.G.[Hong-Gang],
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IP(25), No. 8, August 2016, pp. 3931-3946.
IEEE DOI 1608
BibRef
Earlier:
Joint patch and multi-label learning for facial action unit detection,
CVPR15(2207-2216)
IEEE DOI 1510
face recognition BibRef

Chu, W.S.[Wen-Sheng], de la Torre, F.[Fernando], Cohn, J.F.[Jeffrey F.],
Learning Spatial and Temporal Cues for Multi-Label Facial Action Unit Detection,
FG17(25-32)
IEEE DOI 1707
Context, Correlation, Face, Feature extraction, Gold, Image color analysis, Videos BibRef

Zhao, K.[Kaili], Chu, W.S.[Wen-Sheng], Zhang, H.G.[Hong-Gang],
Deep Region and Multi-label Learning for Facial Action Unit Detection,
CVPR16(3391-3399)
IEEE DOI 1612
BibRef

Girard, J.M., Cohn, J.F., Jeni, L.A.[László A.], Lucey, S., de la Torre, F.,
How much training data for facial action unit detection?,
FG15(1-8)
IEEE DOI 1508
face recognition BibRef

Nicolle, J.[Jérémie], Bailly, K.[Kévin], Chetouani, M.[Mohamed],
Real-time facial action unit intensity prediction with regularized metric learning,
IVC(52), No. 1, 2016, pp. 1-14.
Elsevier DOI 1609
Facial expression BibRef

Nicolle, J.[Jérémie], Bailly, K.[Kévin], Rapp, V.[Vincent], Chetouani, M.[Mohamed],
Locating facial landmarks with binary map cross-correlations,
ICIP13(2978-2982)
IEEE DOI 1402
LBP; LPQ; binary maps; facial landmarks; shape model BibRef

Zeng, J., Chu, W.S.[Wen-Sheng], de la Torre, F.[Fernando], Cohn, J.F.[Jeffery F.], Xiong, Z.,
Confidence Preserving Machine for Facial Action Unit Detection,
IP(25), No. 10, October 2016, pp. 4753-4767.
IEEE DOI 1610
BibRef
Earlier: ICCV15(3622-3630)
IEEE DOI 1602
face recognition. Boosting BibRef

Chu, W.S.[Wen-Sheng], de la Torre, F.[Fernando], Cohn, J.F.[Jeffery F.],
Selective Transfer Machine for Personalized Facial Expression Analysis,
PAMI(39), No. 3, March 2017, pp. 529-545.
IEEE DOI 1702
BibRef
Earlier:
Selective Transfer Machine for Personalized Facial Action Unit Detection,
CVPR13(3515-3522)
IEEE DOI 1309
Facial action unit detection; SVM; domain adaptation BibRef

Wang, S.F.[Shang-Fei], Gan, Q.[Quan], Ji, Q.A.[Qi-Ang],
Expression-assisted facial action unit recognition under incomplete AU annotation,
PR(61), No. 1, 2017, pp. 78-91.
Elsevier DOI 1609
AU recognition BibRef

Rahman, A.K.M.M.[A.K.M. Mahbubur], Anam, A.I.[Asm Iftekhar], Yeasin, M.[Mohammed],
A Unified Framework for Dividing and Predicting a Large Set of Action Units,
AffCom(7), No. 4, October 2016, pp. 311-325.
IEEE DOI 1612
Computational modeling BibRef

Rudovic, O.[Ognjen], Pantic, M.[Maja], Patras, I.Y.[Ioannis Yiannis],
Coupled Gaussian Processes for Pose-Invariant Facial Expression Recognition,
PAMI(35), No. 6, June 2013, pp. 1357-1369.
IEEE DOI 1305
BibRef
Earlier: A1, A3, A2:
Coupled Gaussian Process Regression for Pose-Invariant Facial Expression Recognition,
ECCV10(II: 350-363).
Springer DOI 1009
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Earlier: A1, A3, A2:
Regression-Based Multi-view Facial Expression Recognition,
ICPR10(4121-4124).
IEEE DOI 1008
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Eleftheriadis, S.[Stefanos], Rudovic, O.[Ognjen], Pantic, M.[Maja],
Discriminative Shared Gaussian Processes for Multiview and View-Invariant Facial Expression Recognition,
IP(24), No. 1, January 2015, pp. 189-204.
IEEE DOI 1502
BibRef
Earlier:
View-Constrained Latent Variable Model for Multi-view Facial Expression Classification,
ISVC14(II: 292-303).
Springer DOI 1501
BibRef
Earlier:
Shared Gaussian Process Latent Variable Model for Multi-view Facial Expression Recognition,
ISVC13(I:527-538).
Springer DOI 1310
Gaussian processes BibRef

Eleftheriadis, S.[Stefanos], Rudovic, O.[Ognjen], Pantic, M.[Maja],
Joint Facial Action Unit Detection and Feature Fusion: A Multi-Conditional Learning Approach,
IP(25), No. 12, December 2016, pp. 5727-5742.
IEEE DOI 1612
BibRef
Earlier:
Multi-conditional Latent Variable Model for Joint Facial Action Unit Detection,
ICCV15(3792-3800)
IEEE DOI 1602
Bayes methods BibRef

Eleftheriadis, S.[Stefanos], Rudovic, O.[Ognjen], Deisenroth, M.P.[Marc Peter], Pantic, M.[Maja],
Gaussian Process Domain Experts for Modeling of Facial Affect,
IP(26), No. 10, October 2017, pp. 4697-4711.
IEEE DOI 1708
BibRef
Earlier:
Variational Gaussian Process Auto-Encoder for Ordinal Prediction of Facial Action Units,
ACCV16(II: 154-170).
Springer DOI 1704
BibRef
Earlier:
Gaussian Process Domain Experts for Model Adaptation in Facial Behavior Analysis,
Affect16(1469-1477)
IEEE DOI 1612
Gaussian processes, emotion recognition, face recognition, Gaussian process domain, facial behavior analysis, facial expression analysis, probabilistic framework, supervised domain adaptation, Adaptation models, Analytical models, Computational modeling, Context, Data models, Gold, Training, Domain adaptation, Gaussian processes, multi-view facial expression recognition, multiple AU detection BibRef

Yang, S.[Shuang], Rudovic, O.[Ognjen], Pavlovic, V.[Vladimir], Pantic, M.[Maja],
Personalized Modeling of Facial Action Unit Intensity,
ISVC14(II: 269-281).
Springer DOI 1501
BibRef

Rudovic, O.[Ognjen], Pavlovic, V.[Vladimir], Pantic, M.[Maja],
Context-Sensitive Dynamic Ordinal Regression for Intensity Estimation of Facial Action Units,
PAMI(37), No. 5, May 2015, pp. 944-958.
IEEE DOI 1504
BibRef
Earlier:
Context-Sensitive Conditional Ordinal Random Fields for Facial Action Intensity Estimation,
HACI13(492-499)
IEEE DOI 1403
BibRef
And:
Automatic Pain Intensity Estimation with Heteroscedastic Conditional Ordinal Random Fields,
ISVC13(II:234-243).
Springer DOI 1311
BibRef
Earlier:
Kernel Conditional Ordinal Random Fields for Temporal Segmentation of Facial Action Units,
Face12(II: 260-269).
Springer DOI 1210
BibRef
Earlier:
Multi-Output Laplacian Dynamic Ordinal Regression for Facial Expression Recognition and Intensity Estimation,
CVPR12(2634-2641).
IEEE DOI 1208
Context. emotion recognition See also Structured Output Ordinal Regression for Dynamic Facial Emotion Intensity Prediction. BibRef

Walecki, R.[Robert], Rudovic, O.[Ognjen], Pavlovic, V.[Vladimir], Schuller, B., Pantic, M.[Maja],
Deep Structured Learning for Facial Action Unit Intensity Estimation,
CVPR17(5709-5718)
IEEE DOI 1711
Data models, Estimation, Face, Feature extraction, Gold, Machine, learning BibRef

Walecki, R.[Robert], Rudovic, O.[Ognjen], Pantic, M.[Maja], Pavlovic, V.[Vladimir], Cohn, J.F.,
A Framework for Joint Estimation and Guided Annotation of Facial Action Unit Intensity,
Affect16(1460-1468)
IEEE DOI 1612
BibRef

Walecki, R.[Robert], Rudovic, O.[Ognjen], Pavlovic, V.[Vladimir], Pantic, M.[Maja],
Variable-state Latent Conditional Random Field models for facial expression analysis,
IVC(58), No. 1, 2017, pp. 25-37.
Elsevier DOI 1703
BibRef
And:
Copula Ordinal Regression for Joint Estimation of Facial Action Unit Intensity,
CVPR16(4902-4910)
IEEE DOI 1612
Facial expression BibRef

Sandbach, G., Zafeiriou, S.P., Pantic, M.,
Markov Random Field Structures for Facial Action Unit Intensity Estimation,
SocialInter13(738-745)
IEEE DOI 1403
Markov processes BibRef

Walecki, R., Rudovic, O., Pavlovic, V., Pantic, M.,
Variable-state latent conditional random fields for facial expression recognition and action unit detection,
FG15(1-8)
IEEE DOI 1508
emotion recognition BibRef

Kaltwang, S.[Sebastian], Todorovic, S.[Sinisa], Pantic, M.[Maja],
Latent trees for estimating intensity of Facial Action Units,
CVPR15(296-304)
IEEE DOI 1510
BibRef

Lekdioui, K.[Khadija], Messoussi, R.[Rochdi], Ruichek, Y.[Yassine], Chaabi, Y.[Youness], Touahni, R.[Raja],
Facial decomposition for expression recognition using texture/shape descriptors and SVM classifier,
SP:IC(58), No. 1, 2017, pp. 300-312.
Elsevier DOI 1710
Facial components BibRef


Chang, W.Y., Hsu, S.H., Chien, J.H.,
FATAUVA-Net: An Integrated Deep Learning Framework for Facial Attribute Recognition, Action Unit Detection, and Valence-Arousal Estimation,
FaceWild17(1963-1971)
IEEE DOI 1709
Emotion recognition, Estimation, Face, Face recognition, Feature extraction, Gold, Machine, learning BibRef

Batista, J.C., Albiero, V., Bellon, O.R.P., Silva, L.,
AUMPNet: Simultaneous Action Units Detection and Intensity Estimation on Multipose Facial Images Using a Single Convolutional Neural Network,
FG17(866-871)
IEEE DOI 1707
Databases, Estimation, Face, Gold, Magnetic heads, Optimization BibRef

Zhou, Y., Pi, J., Shi, B.E.,
Pose-Independent Facial Action Unit Intensity Regression Based on Multi-Task Deep Transfer Learning,
FG17(872-877)
IEEE DOI 1707
Estimation, Face, Face recognition, Gold, Hidden Markov models, Neural networks, Training BibRef

Tang, C., Zheng, W., Yan, J., Li, Q., Li, Y., Zhang, T., Cui, Z.,
View-Independent Facial Action Unit Detection,
FG17(878-882)
IEEE DOI 1707
Face, Feature extraction, Gold, Image segmentation, Lips, Neural networks, Training BibRef

He, J., Li, D., Yang, B., Cao, S., Sun, B., Yu, L.,
Multi View Facial Action Unit Detection Based on CNN and BLSTM-RNN,
FG17(848-853)
IEEE DOI 1707
Face, Face recognition, Feature extraction, Gold, Kernel, Machine learning, Training BibRef

Li, W., Abtahi, F., Zhu, Z.,
Action Unit Detection with Region Adaptation, Multi-labeling Learning and Optimal Temporal Fusing,
CVPR17(6766-6775)
IEEE DOI 1711
Face, Feature extraction, Gold, Machine learning, Muscles, Neural networks, Training BibRef

Li, W., Abtahi, F., Zhu, Z., Yin, L.,
EAC-Net: A Region-Based Deep Enhancing and Cropping Approach for Facial Action Unit Detection,
FG17(103-110)
IEEE DOI 1707
Agriculture, Face, Feature extraction, Gold, Lips, Robustness, Training BibRef

Li, X., Chen, S., Jin, Q.,
Facial Action Units Detection with Multi-Features and -AUs Fusion,
FG17(860-865)
IEEE DOI 1707
Face, Face recognition, Feature extraction, Gold, Radio frequency, Support vector machines, Training BibRef

Amirian, M., Kächele, M.[Markus], Palm, G., Schwenker, F.[Friedhelm],
Support Vector Regression of Sparse Dictionary-Based Features for View-Independent Action Unit Intensity Estimation,
FG17(854-859)
IEEE DOI 1707
Dictionaries, Encoding, Estimation, Face, Gold, Matching pursuit algorithms, Shape BibRef

Kachele, M.[Markus], Schwenker, F.[Friedhelm],
Cascaded Fusion of Dynamic, Spatial, and Textural Feature Sets for Person-Independent Facial Emotion Recognition,
ICPR14(4660-4665)
IEEE DOI 1412
Computer architecture BibRef

Kim, E., Vangala, S.,
Deep Action Unit classification using a binned intensity loss and semantic context model,
ICPR16(4136-4141)
IEEE DOI 1705
Convolutional codes, Entropy, Feature extraction, Gold, Neural networks, Semantics, Training BibRef

Tosér, Z.[Zoltán], Jeni, L.A.[László A.], Lorincz, A.[András], Cohn, J.F.[Jeffrey F.],
Deep Learning for Facial Action Unit Detection Under Large Head Poses,
ChaLearn16(III: 359-371).
Springer DOI 1611
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Jaiswal, S., Valstar, M.F.,
Deep learning the dynamic appearance and shape of facial action units,
WACV16(1-8)
IEEE DOI 1606
Computer architecture BibRef

Ruiz, A.[Adria], Van de Weijer, J.[Joost], Binefa, X.[Xavier],
From Emotions to Action Units with Hidden and Semi-Hidden-Task Learning,
ICCV15(3703-3711)
IEEE DOI 1602
BibRef
Earlier:
Regularized Multi-Concept MIL for weakly-supervised facial behavior categorization,
BMVC14(xx-yy).
HTML Version. 1410
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Song, Y., McDuff, D., Vasisht, D., Kapoor, A.,
Exploiting sparsity and co-occurrence structure for action unit recognition,
FG15(1-8)
IEEE DOI 1508
Bayes methods BibRef

Chen, J.[Junkai], Chen, Z.[Zenghai], Chi, Z.[Zheru], Fu, H.[Hong],
Recognition of Facial Action Units with Action Unit Classifiers and an Association Network,
CV4AC14(672-683).
Springer DOI 1504
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Bingol, D.[Deniz], Celik, T.[Turgay], Omlin, C.W.[Christian W.], Vadapalli, H.B.[Hima B.],
Facial action unit intensity estimation using rotation invariant features and regression analysis,
ICIP14(1381-1385)
IEEE DOI 1502
Conferences BibRef

Han, S.H.[Shiz-Hong], Meng, Z.[Zibo], Liu, P.[Ping], Tong, Y.[Yan],
Facial grid transformation: A novel face registration approach for improving facial action unit recognition,
ICIP14(1415-1419)
IEEE DOI 1502
Databases 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

Zhang, X.[Xiao], Mahoor, M.H.[Mohammad H.],
Simultaneous Detection of Multiple Facial Action Units via Hierarchical Task Structure Learning,
ICPR14(1863-1868)
IEEE DOI 1412
Databases BibRef

Jiang, B.[Bihan], Martinez, B.[Brais], Pantic, M.[Maja],
Parametric temporal alignment for the detection of facial action temporal segments,
BMVC14(xx-yy).
HTML Version. 1410
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Khademi, M.[Mahmoud], Morency, L.P.[Louis-Philippe],
Relative facial action unit detection,
WACV14(1090-1095)
IEEE DOI 1406
Databases BibRef

Hsu, G.S.[Gee-Sern], Yeh, S.M.[Shang-Min],
Heterogeneous feature code for expression recognition,
ICIP13(2407-2411)
IEEE DOI 1402
Expression recognition;facial features;feature extraction BibRef

Yuce, A., Sorci, M., Thiran, J.P.,
Improved local binary pattern based action unit detection using morphological and bilateral filters,
FG13(1-7)
IEEE DOI 1309
face recognition BibRef

Yang, S.F.[Song-Fan], An, L.[Le], Bhanu, B., Thakoor, N.,
Improving action units recognition using dense flow-based face registration in video,
FG13(1-8)
IEEE DOI 1309
affine transforms BibRef

Mavadati, S.M.[S. Mohammad], Mahoor, M.H.[Mohammad H.], Bartlett, K.[Kevin], Trinh, P.[Philip],
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IEEE DOI 1302
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Selpi, Wilhelm, T.[Torsten], Jansson, M.[Marcus], Hagstrom, L.[Li], Brandin, N.[Niklas], Andersson, M.[Magnus], Gronvall, J.F.[John-Fredrik],
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Cosker, D.[Darren], Krumhuber, E.[Eva], Hilton, A.[Adrian],
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IEEE DOI 1201
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Gehrig, T.[Tobias], Al-Halah, Z., Ekenel, H.K.[Hazim Kemal], Stiefelhagen, R.,
Action unit intensity estimation using hierarchical partial least squares,
FG15(1-6)
IEEE DOI 1508
Gaussian processes BibRef

Gehrig, T.[Tobias], Ekenel, H.K.[Hazim Kemal],
Facial action unit detection using kernel partial least squares,
BenchFace11(2092-2099).
IEEE DOI 1201
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CVPR4HB11(1-6).
IEEE DOI 1106
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Jiang, B.[Bihan], Martinez, B.[Brais], Valstar, M.F.[Michel F.], Pantic, M.[Maja],
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ICPR14(1776-1781)
IEEE DOI 1412
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Jiang, B.[Bihan], Valstar, M.F.[Michel F.], Pantic, M.[Maja],
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FG11(314-321).
IEEE DOI 1103
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Mahoor, M.H.[Mohammad H.], Zhou, M.[Mu], Veon, K.L.[Kevin L.], Mavadati, S.M.[S. Mohammad], Cohn, J.F.[Jeffrey F.],
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FG11(336-342).
IEEE DOI 1103
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Senechal, T.[Thibaud], Rapp, V.[Vincent], Salam, H.[Hanan], Seguier, R.[Renaud], Bailly, K.[Kevin], Prevost, L.[Lionel],
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FG11(860-865).
IEEE DOI 1103
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Simon, T.[Tomas], Nguyen, M.H.[Minh Hoai], de la Torre, F.[Fernando], Cohn, J.F.[Jeffrey F.],
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CVPR10(2737-2744).
IEEE DOI 1006
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Zor, C.[Cemre], Windeatt, T.[Terry],
Upper Facial Action Unit Recognition,
ICB09(239-248).
Springer DOI 0906
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Windeatt, T.[Terry], Dias, K.[Kaushala],
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CIARP08(551-559).
Springer DOI 0809
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Liu, P.[Peng], Yin, L.J.[Li-Jun],
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FG15(1-6)
IEEE DOI 1508
emotion recognition BibRef

Reale, M.[Michael], Liu, P.[Peng], Yin, L.J.[Li-Jun],
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Sun, Y.[Yi], Reale, M.[Michael], Yin, L.J.[Li-Jun],
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FG08(1-8).
IEEE DOI 0809
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Tong, Y.[Yan], Chen, J.X.[Ji-Xu], Ji, Q.A.[Qi-Ang],
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IEEE DOI 0906
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Zhang, L.[Lei], Tong, Y.[Yan], Ji, Q.A.[Qi-Ang],
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ECCV08(II: 706-719).
Springer DOI 0810
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ICPR08(1-4).
IEEE DOI 0812
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de Campos, C.P.[Cassio P.], Tong, Y.[Yan], Ji, Q.A.[Qi-Ang],
Constrained Maximum Likelihood Learning of Bayesian Networks for Facial Action Recognition,
ECCV08(III: 168-181).
Springer DOI 0810
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de Campos, C.P.[Cassio P.], Ji, Q.A.[Qi-Ang],
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ICPR08(1-4).
IEEE DOI 0812
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Xu, S.A.[Shu-Ang], Jia, Y.D.[Yun-De], Zhang, X.X.[Xiao-Xun],
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ICIP06(2057-2060).
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McCall, J.C.[Joel C.], Trivedi, M.M.[Mohan M.],
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ICPR04(III: 958-964).
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McCall, J.C.[Joel C.], Trivedi, M.M.[Mohan M.],
Facial Action Coding Using Multiple Visual Cues and a Hierarchy of Particle Filters,
V4HCI06(150).
IEEE DOI 0609
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Whitehill, J., Omlin, C.W.,
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FGR06(97-101).
IEEE DOI 0604
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Whitehill, J., Omlin, C.W.,
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FGR06(357-362).
IEEE DOI 0604
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Tong, Y.[Yan], Liao, W.H.[Wen-Hui], Ji, Q.A.[Qi-Ang],
Inferring Facial Action Units with Causal Relations,
CVPR06(II: 1623-1630).
IEEE DOI 0606
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Lucey, P.[Patrick], Lucey, S.[Simon], Cohn, J.F.[Jeffrey F.],
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DICTA10(255-261).
IEEE DOI 1012
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Wang, Y.[Yang], Lucey, S.[Simon], Cohn, J.F.[Jeffrey F.],
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NRTL07(1-8).
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BibRef

de la Torre, F.[Fernando], Campoy, J.[Joan], Ambadar, Z.[Zara], Cohn, J.F.[Jeffrey F.],
Temporal Segmentation of Facial Behavior,
ICCV07(1-8).
IEEE DOI 0710
BibRef

Lucey, S., Matthews, I., Hu, C.B.[Chang-Bo], Ambadar, Z., de la Torre, F., Cohn, J.F.,
AAM Derived Face Representations for Robust Facial Action Recognition,
FGR06(155-162).
IEEE DOI
HTML Version. 0604
See also Multi-View AAM Fitting and Camera Calibration. BibRef

Sifakis, E.[Eftychios], Fedkiw, R.[Ron],
Facial Muscle Activations from Motion Capture,
CVPR05(II: 1195).
IEEE DOI 0507
BibRef

Wang, H.C.[Hong-Cheng], Ahuja, N.,
Facial expression decomposition,
ICCV03(958-965).
IEEE DOI 0311
BibRef

Fasel, B.[Beat], Luettin, J.[Juergen],
Recognition of Asymmetric Facial Action Unit Activities and Intensities,
ICPR00(Vol I: 1100-1103).
IEEE DOI 0009
BibRef

Colmenarez, A.J.[Antonio J.], Frey, B.J.[Brendan J.], Huang, T.S.[Thomas S.],
A Probabilistic Framework for Embedded Face and Facial Expression Recognition,
CVPR99(I: 592-597).
IEEE DOI BibRef 9900
And:
Embedded Face and Facial Expression Recognition,
ICIP99(I:633-637).
IEEE DOI BibRef

Frey, B.J.[Brendan J.], Colmenarez, A.J., Huang, T.S.,
Mixtures of Local Linear Subspaces for Face Recognition,
CVPR98(32-37).
IEEE DOI BibRef 9800

Weng, J.[John], Hwang, W.S.[Wey-Shiuan],
Sensorimotor Action Sequence Learning with Application to Face Recognition Under Discourse,
ICPR98(Vol I: 252-254).
IEEE DOI 9808
BibRef

Saji, H.[Hitoshi], Nakatani, H.[Hiromasa], Ohta, H.[Hiroshi],
Recognition of Facial Expressions Using Muscle-Based Feature Models,
ICPR98(Vol II: 1379-1381).
IEEE DOI 9808
BibRef

Ishikawa, T.[Takahiro], Yazaki, K.[Kazuhiko], Sera, H.[Hajime], Morishima, S.[Shigeo], Terzopoulos, D.[Demetri],
Facial Muscle Parameter Decision from 2D Frontal Image,
ICPR98(Vol I: 160-162).
IEEE DOI 9808
BibRef

Eisert, P., and Girod, B.,
Model-Based Estimation of Facial Expression Parameters from Image Sequences,
ICIP97(II: 418-421).
IEEE DOI BibRef 9700

Chapter on Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics continues in
Facial Feature Tracking for Expressions .


Last update:Nov 18, 2017 at 20:56:18