22.3.6.2 Emotion Recognition from Face Images

Chapter Contents (Back)
Application, Faces. Faces, Emotions. Emotion Recognition.
See also Emotion Recognition, Deep Learning.
See also Emotion Recognition, Survey, General, Review, Datasets, Database.
See also Multi-Modal Emotion, Multimodal Emotion Recognition.
See also Personality, Traits, Mood, Deception, Diagnosis Analysis.
See also Emotion Recognition, Body Gestures, Body Language.
See also Face Expression Recognition and Analysis, Facial Expression Analysis, Facial Expressions.
See also Audio-Visual Emotion, Audiovisual Emotion Recognition. Synthesis:
See also Emotions in Face Animation, Video Face Synthesis.

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Senechal, T.[Thibaud], Bailly, K.[Kevin], Prevost, L.[Lionel],
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Majumder, A.[Anima], Behera, L.[Laxmidhar], Subramanian, V.K.[Venkatesh K.],
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Elsevier DOI 1312
Facial expression analysis BibRef

Samadani, A.A., Gorbet, R., Kulic, D.,
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Dahmane, M.[Mohamed], Meunier, J.[Jean],
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MultMed(16), No. 6, October 2014, pp. 1574-1584.
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Earlier:
Individual Feature-Appearance for Facial Action Recognition,
ICIAR11(II: 233-242).
Springer DOI 1106
emotion recognition BibRef

Dahmane, M.[Mohamed], Meunier, J.[Jean],
Emotion recognition using dynamic grid-based HoG features,
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Agrawal, D.D.[Dev Drume], Dubey, S.R.[Shiv Ram], Jalal, A.S.[Anand Singh],
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IEEE DOI 2406
Computational modeling, Visualization, Data models, Brain modeling, Testing, Emotion recognition, Affect modelling, arousal, valence BibRef

Cruz, A.C., Bhanu, B., Thakoor, N.S.,
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Lee, S.H.[Seung Ho], Plataniotis, K.N.K.[K.N. Kostas], Ro, Y.M.[Yong Man],
Intra-Class Variation Reduction Using Training Expression Images for Sparse Representation Based Facial Expression Recognition,
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IEEE DOI 1412
face recognition BibRef

Lee, S.H.[Seung Ho], Ro, Y.M.[Yong Man],
Partial Matching of Facial Expression Sequence Using Over-Complete Transition Dictionary for Emotion Recognition,
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Lee, S.H.[Seung Ho], Baddar, W.J.[Wissam J.], Ro, Y.M.[Yong Man],
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Elsevier DOI 1603
Facial expression recognition (FER) BibRef

Kim, D.H.[Dae Hoe], Baddar, W.J.[Wissam J.], Jang, J., Ro, Y.M.[Yong Man],
Multi-Objective Based Spatio-Temporal Feature Representation Learning Robust to Expression Intensity Variations for Facial Expression Recognition,
AffCom(10), No. 2, April 2019, pp. 223-236.
IEEE DOI 1906
BibRef
Earlier: A2, A1, A4, Only:
Learning Features Robust to Image Variations with Siamese Networks for Facial Expression Recognition,
MMMod17(I: 189-200).
Springer DOI 1701
Feature extraction, Face recognition, Robustness, Machine learning, Training, long short-term memory (LSTM) BibRef

Kim, H.I.[Hyung-Il], Lee, S.H.[Seung Ho], Ro, Y.M.[Yong Man],
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ICIP15(4027-4031)
IEEE DOI 1512
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Earlier:
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IEEE DOI 1507
emotion recognition BibRef

Savran, A., Gur, R., Verma, R.,
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CDC4CV13(75-82)
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IEEE DOI 1604
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IEEE DOI 1604
emotion recognition BibRef

Gao, L.[Lei], Qi, L.[Lin], Guan, L.[Ling],
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IEEE_Int_Sys(31), No. 5, September 2016, pp. 32-39.
IEEE DOI 1610
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Sparsity preserving multiple canonical correlation analysis with visual emotion recognition to multi-feature fusion,
ICIP15(2710-2714)
IEEE DOI 1512
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Gunes, H.[Hatice], Hung, H.[Hayley],
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Elsevier DOI 1612
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Zhao, S., Yao, H., Gao, Y., Ji, R., Ding, G.,
Continuous Probability Distribution Prediction of Image Emotions via Multitask Shared Sparse Regression,
MultMed(19), No. 3, March 2017, pp. 632-645.
IEEE DOI 1702
Distance measurement BibRef

Zhao, S., Ding, G., Gao, Y., Zhao, X., Tang, Y., Han, J., Yao, H., Huang, Q.,
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AffCom(11), No. 4, October 2020, pp. 574-587.
IEEE DOI 2011
Visualization, Feature extraction, Probability distribution, Training, Task analysis, Dictionaries, Learning systems, multi-feature fusion BibRef

Zhao, S., Yao, H., Gao, Y., Ding, G., Chua, T.,
Predicting Personalized Image Emotion Perceptions in Social Networks,
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IEEE DOI 1812
Feature extraction, Social network services, Visualization, Bridges, Context, Meteorology, Clouds, Personalized image emotion, heypergraph learning BibRef

Xia, R., Liu, Y.,
A Multi-Task Learning Framework for Emotion Recognition Using 2D Continuous Space,
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IEEE DOI 1703
Acoustics BibRef

Dingli, A.[Alexiei], Giordimaina, A.[Andreas],
Webcam-based detection of emotional states,
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Jiang, R.[Richard], Ho, A.T.S.[Anthony T.S.], Cheheb, I.[Ismahane], Al-Maadeed, N.[Noor], Al-Maadeed, S.[Somaya], Bouridane, A.[Ahmed],
Emotion recognition from scrambled facial images via many graph embedding,
PR(67), No. 1, 2017, pp. 245-251.
Elsevier DOI 1704
Facial expression BibRef

Mistry, K., Zhang, L., Neoh, S.C., Lim, C.P., Fielding, B.,
A Micro-GA Embedded PSO Feature Selection Approach to Intelligent Facial Emotion Recognition,
Cyber(47), No. 6, June 2017, pp. 1496-1509.
IEEE DOI 1706
Convergence, Emotion recognition, Face recognition, Feature extraction, Genetic algorithms, Optimization, Search problems, Ensemble classifier, facial expression recognition, feature selection, particle swarm optimization, (PSO) BibRef

Wu, B., Jia, J., Yang, Y., Zhao, P., Tang, J., Tian, Q.,
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MultMed(19), No. 7, July 2017, pp. 1670-1684.
IEEE DOI 1706
Computer science, Correlation, Feature extraction, Learning systems, Social network services, Support vector machines, Visualization, Emotion, image, user, demographics BibRef

Rathee, N.[Neeru], Ganotra, D.[Dinesh],
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IJCVR(7), No. 6, 2017, pp. 669-691.
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IEEE DOI 1712
Face, Face recognition, Shape, Solid modeling, Training. emotion recognition BibRef

Li, X., Rao, Y., Xie, H., Lau, R.Y.K., Yin, J., Wang, F.L.,
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IEEE DOI 1712
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Agarwal, S.[Swapna], Santra, B.[Bikash], Mukherjee, D.P.[Dipti Prasad],
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IEICE(E101-D), No. 5, May 2018, pp. 1317-1324.
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Elsevier DOI 1805
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IEEE DOI 1806
Emotion recognition, Feature extraction, Image recognition, Knowledge transfer, Semantics, Training, Visualization, zero-shot learning BibRef

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IEEE DOI 1809
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Schuller, D., Schuller, B.W.,
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IEEE DOI 1810
Artificial intelligence, Emotion recognition, Machine learning, Learning systems, Artificial Emotional Intelligence, future of AI BibRef

Zhang, H.M.[Hai-Min], Xu, M.[Min],
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IEEE DOI 2303
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IEEE DOI 1810
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IEEE DOI 1903
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Elsevier DOI 1908
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Springer DOI 1901
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IEEE DOI 2104
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Videos, Feature extraction, Emotion recognition, Task analysis, Visualization, Psychology, Computer architecture, machine vision BibRef

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Videos, Usability, Tools, Standards, Real-time systems, Support vector machines, Affective computing, pattern recognition BibRef

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Making emotions transparent: Google Glass helps autistic kids understand facial expressions through augmented-reaiity therapy,
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Springer DOI 2005
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AffCom(11), No. 2, April 2020, pp. 258-271.
IEEE DOI 2006
Computational modeling, Mathematical model, Atmospheric measurements, Particle measurements, Synchronization, cross-recurrence quantification analysis BibRef

Mumenthaler, C., Sander, D., Manstead, A.S.R.,
Emotion Recognition in Simulated Social Interactions,
AffCom(11), No. 2, April 2020, pp. 308-312.
IEEE DOI 2006
Avatars, Emotion recognition, Face recognition, Cognitive processes, Emotion recognition, cognitive appraisal, social interaction BibRef

Canales, L., Strapparava, C., Boldrini, E., Martínez-Barco, P.,
Intensional Learning to Efficiently Build Up Automatically Annotated Emotion Corpora,
AffCom(11), No. 2, April 2020, pp. 335-347.
IEEE DOI 2006
Semantics, Standards, Computational modeling, Emotion recognition, Proposals, Reliability, Affective computing, corpora annotation, textual emotion recognition BibRef

Savakar, D.G.[Dayanand G.], Hosur, R.[Ravi],
The 3D Emotion Recognition Using SVM and HoG Features,
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Pipelined Neural Networks for Phrase-Level Sentiment Intensity Prediction,
AffCom(11), No. 3, July 2020, pp. 447-458.
IEEE DOI 2008
Artificial neural networks, Predictive models, Switches, Learning systems, Linear regression, Prediction algorithms, neural network BibRef

Yi, Y.[Yun], Wang, H.L.[Han-Li], Li, Q.Y.[Qin-Yu],
Affective Video Content Analysis With Adaptive Fusion Recurrent Network,
MultMed(22), No. 9, September 2020, pp. 2454-2466.
IEEE DOI 2008
Adaptive systems, Correlation, Computer science, Motion pictures, Hidden Markov models, Support vector machines, Task analysis, multiple modalities BibRef

Steephen, J.E., Obbineni, S.C., Kummetha, S., Bapi, R.S.,
HED-ID: An Affective Adaptation Model Explaining the Intensity-Duration Relationship of Emotion,
AffCom(11), No. 4, October 2020, pp. 736-750.
IEEE DOI 2011
Affective adaptation, intensity and duration, modeling human emotion, region-ß paradox BibRef

Yannakakis, G.N., Cowie, R., Busso, C.,
The Ordinal Nature of Emotions: An Emerging Approach,
AffCom(12), No. 1, January 2021, pp. 16-35.
IEEE DOI 2103
Affective computing, Psychology, Reliability theory, Computational modeling, Task analysis, Tools, Emotion annotation, preference learning BibRef

Muszynski, M., Tian, L., Lai, C., Moore, J.D., Kostoulas, T., Lombardo, P., Pun, T., Chanel, G.,
Recognizing Induced Emotions of Movie Audiences from Multimodal Information,
AffCom(12), No. 1, January 2021, pp. 36-52.
IEEE DOI 2103
Motion pictures, Emotion recognition, Feature extraction, Physiology, Databases, Brain modeling, Analytical models, crowdsourcing BibRef

Kulkarni, K.[Kaustubh], Corneanu, C.A.[Ciprian Adrian], Ofodile, I.[Ikechukwu], Escalera, S.[Sergio], Baró, X.[Xavier], Hyniewska, S.[Sylwia], Allik, J.[Jüri], Anbarjafari, G.[Gholamreza],
Automatic Recognition of Facial Displays of Unfelt Emotions,
AffCom(12), No. 2, April 2021, pp. 377-390.
IEEE DOI 2106
Emotion recognition, Face recognition, Feature extraction, Face, Psychology, Observers, Trajectory, Affective computing, human behaviour analysis BibRef

Aylett, R.[Ruth], Ritter, C.[Christopher], Lim, M.Y.[Mei Yii], Broz, F.[Frank], McKenna, P.E.[Peter E.], Keller, I.[Ingo], Rajendran, G.[Gnanathusharan],
An Architecture for Emotional Facial Expressions as Social Signals,
AffCom(12), No. 2, April 2021, pp. 293-305.
IEEE DOI 2106
Appraisal, Computer architecture, Robots, Face, Games, Computational modeling, Mirrors, Intelligent agents, cognitive informatics BibRef

Mittal, T.[Trisha], Bera, A.[Aniket], Manocha, D.[Dinesh],
Multimodal and Context-Aware Emotion Perception Model With Multiplicative Fusion,
MultMedMag(28), No. 2, April 2021, pp. 67-75.
IEEE DOI 2107
Emotion recognition, Context modeling, Computational modeling, Semantics, Feature extraction, Measurement, Additives, Perceived Emotion BibRef

Mittal, T., Guhan, P., Bhattacharya, U., Chandra, R., Bera, A.[Aniket], Manocha, D.[Dinesh],
EmotiCon: Context-Aware Multimodal Emotion Recognition Using Frege's Principle,
CVPR20(14222-14231)
IEEE DOI 2008
Emotion recognition, Videos, Psychology, TV, Semantics, Databases, Benchmark testing BibRef

Wang, X.Z.[Xin-Zhi], Chang, Y.D.[Yu-Dong], Sugumaran, V.[Vijayan], Luo, X.F.[Xiang-Feng], Wang, P.[Peng], Zhang, H.[Hui],
Implicit Emotion Relationship Mining Based on Optimal and Majority Synthesis From Multimodal Data Prediction,
MultMedMag(28), No. 2, April 2021, pp. 96-105.
IEEE DOI 2107
Emotion recognition, Predictive models, Data models, Computational modeling, Psychology, Feature extraction, Brain modeling BibRef

Yin, G.H.[Guang-Hao], Sun, S.Q.[Shou-Qian], Zhang, H.[Hui], Yu, D.[Dian], Li, C.[Chao], Zhang, K.J.[Ke-Jun], Zou, N.[Ning],
User Independent Emotion Recognition with Residual Signal-Image Network,
ICIP19(3277-3281)
IEEE DOI 1910
Emotion Recognition, Multi-feature Fusion, Residual Signal Image Network BibRef

Li, H.Y.[Hang-Yu], Wang, N.N.[Nan-Nan], Yang, X.[Xi], Gao, X.B.[Xin-Bo],
CRS-CONT: A Well-Trained General Encoder for Facial Expression Analysis,
IP(31), 2022, pp. 4637-4650.
IEEE DOI 2207
Face recognition, Task analysis, Feature extraction, Training data, Training, Representation learning, Data mining, coarse-contrastive learning BibRef

Du, Z.Y.[Zheng-Yin], Wu, S.[Suowei], Huang, D.[Di], Li, W.X.[Wei-Xin], Wang, Y.H.[Yun-Hong],
Spatio-Temporal Encoder-Decoder Fully Convolutional Network for Video-Based Dimensional Emotion Recognition,
AffCom(12), No. 3, July 2021, pp. 565-578.
IEEE DOI 2109
Emotion recognition, Convolution, Decoding, Feature extraction, Videos, Visualization, Task analysis, temporal intermediate supervision BibRef

Li, W.X.[Wei-Xin], Dong, X.[Xuan], Wang, Y.H.[Yun-Hong],
Human Emotion Recognition With Relational Region-Level Analysis,
AffCom(14), No. 1, January 2023, pp. 650-663.
IEEE DOI 2303
Emotion recognition, Faces, Feature extraction, Face recognition, Semantics, Geometry, Target recognition, Human emotion recognition, emotion label dependency modeling BibRef

Fujii, K.[Katsuya], Sugimura, D.[Daisuke], Hamamoto, T.[Takayuki],
Hierarchical Group-Level Emotion Recognition,
MultMed(23), 2021, pp. 3892-3906.
IEEE DOI 2110
Emotion recognition, Faces, Facial features, Visualization, Semantics, Face recognition, Feature extraction, scene features BibRef

Pei, E.[Ercheng], Oveneke, M.C.[Meshia Cédric], Zhao, Y.[Yong], Jiang, D.M.[Dong-Mei], Sahli, H.[Hichem],
Monocular 3D Facial Expression Features for Continuous Affect Recognition,
MultMed(23), 2021, pp. 3540-3550.
IEEE DOI 2110
Face recognition, Feature extraction, Solid modeling, Emotion recognition, Optical imaging, Strain, continuous affect recognition BibRef

Wang, S.F.[Shang-Fei], Peng, G.Z.[Guo-Zhu], Zheng, Z.Q.[Zhuang-Qiang], Xu, Z.W.[Zhi-Wei],
Capturing Emotion Distribution for Multimedia Emotion Tagging,
AffCom(12), No. 4, October 2021, pp. 821-831.
IEEE DOI 2112
Tagging, Streaming media, Multimedia databases, Media, Computational modeling, Adversarial machine learning, joint label distribution BibRef

Ghosh, S.[Surjya], Ganguly, N.[Niloy], Mitra, B.[Bivas], De, P.[Pradipta],
Designing an Experience Sampling Method for Smartphone Based Emotion Detection,
AffCom(12), No. 4, October 2021, pp. 913-927.
IEEE DOI 2112
Smart phones, Behavioral sciences, Sensors, Time-frequency analysis, Mobile handsets, Sampling methods, emotion detection BibRef

Zhang, J.[Jing], Liu, X.Y.[Xin-Yu], Wang, Z.[Zhe], Yang, H.[Hai],
Graph-Based Object Semantic Refinement for Visual Emotion Recognition,
CirSysVideo(32), No. 5, May 2022, pp. 3036-3049.
IEEE DOI 2205
Visualization, Semantics, Feature extraction, Emotion recognition, Analytical models, Predictive models, Neural networks, visual emotion recognition BibRef

Ayari, N., Abdelkawy, H., Chibani, A., Amirat, Y.,
Hybrid Model-Based Emotion Contextual Recognition for Cognitive Assistance Services,
Cyber(52), No. 5, May 2022, pp. 3567-3576.
IEEE DOI 2206
Emotion recognition, Robots, Ontologies, Hidden Markov models, Cognition, Face recognition, Context modeling, ubiquitous robotics BibRef

Yang, J.Y.[Jing-Yuan], Li, J.[Jie], Li, L.[Leida], Wang, X.M.[Xiu-Mei], Ding, Y.X.[Yu-Xuan], Gao, X.B.[Xin-Bo],
Seeking Subjectivity in Visual Emotion Distribution Learning,
IP(31), 2022, pp. 5189-5202.
IEEE DOI 2208
Visualization, Appraisal, Psychology, Feature extraction, Task analysis, Prediction algorithms, Annotations, memory network BibRef

Heimerl, A.[Alexander], Weitz, K.[Katharina], Baur, T.[Tobias], André, E.[Elisabeth],
Unraveling ML Models of Emotion With NOVA: Multi-Level Explainable AI for Non-Experts,
AffCom(13), No. 3, July 2022, pp. 1155-1167.
IEEE DOI 2209
Annotations, Machine learning, Computational modeling, Tools, Predictive models, Data models, Databases, annotation tools BibRef

Dindar, M.[Muhterem], Järvelä, S.[Sanna], Ahola, S.[Sara], Huang, X.H.[Xiao-Hua], Zhao, G.Y.[Guo-Ying],
Leaders and Followers Identified by Emotional Mimicry During Collaborative Learning: A Facial Expression Recognition Study on Emotional Valence,
AffCom(13), No. 3, July 2022, pp. 1390-1400.
IEEE DOI 2209
Collaboration, Collaborative work, Task analysis, Emotion recognition, Face recognition, Leadership, multimodality BibRef

Xing, S.[Songlong], Mai, S.[Sijie], Hu, H.F.[Hai-Feng],
Adapted Dynamic Memory Network for Emotion Recognition in Conversation,
AffCom(13), No. 3, July 2022, pp. 1426-1439.
IEEE DOI 2209
Emotion recognition, Adaptation models, Task analysis, Computational modeling, Psychology, Convolution, Memory modules, multimodal feature fusion BibRef

Fu, Y.H.[Ya-Hui], Okada, S.[Shogo], Wang, L.[Longbiao], Guo, L.[Lili], Song, Y.[Yaodong], Liu, J.X.[Jia-Xing], Dang, J.[Jianwu],
Context- and Knowledge-Aware Graph Convolutional Network for Multimodal Emotion Recognition,
MultMedMag(29), No. 3, July 2022, pp. 91-100.
IEEE DOI 2209
Emotion recognition, Context modeling, Semantics, Oral communication, Knowledge based systems, Task analysis, Social networking (online) BibRef

Lo, L.[Ling], Xie, H.X.[Hong-Xia], Shuai, H.H.[Hong-Han], Cheng, W.H.[Wen-Huang],
Facial Chirality: From Visual Self-Reflection to Robust Facial Feature Learning,
MultMed(24), 2022, pp. 4275-4284.
IEEE DOI 2210
Faces, Feature extraction, Transformers, Reflection, Robustness, Facial features, Face recognition, Facial expression, vision transformer BibRef

Lazarou, I.[Ilias], Kesidis, A.L.[Anastasios L.], Hloupis, G.[George], Tsatsaris, A.[Andreas],
Panic Detection Using Machine Learning and Real-Time Biometric and Spatiotemporal Data,
IJGI(11), No. 11, 2022, pp. xx-yy.
DOI Link 2212
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Smith, G.M.[Geneva M.], Carette, J.[Jacques],
What Lies Beneath: A Survey of Affective Theory Use in Computational Models of Emotion,
AffCom(13), No. 4, October 2022, pp. 1793-1812.
IEEE DOI 2212
Emotion recognition, Training, Task analysis, Protocols, Mood, Brain modeling, Software, Affective computing, psychology BibRef

Wang, Z.L.[Zi-Li], Lao, L.J.[Ling-Jie], Zhang, X.Y.[Xiao-Ya], Li, Y.[Yong], Zhang, T.[Tong], Cui, Z.[Zhen],
Context-dependent emotion recognition,
JVCIR(89), 2022, pp. 103679.
Elsevier DOI 2212
Context-based Emotion Recognition, Tubal Transformer, Hierarchical Fusion, Affective Computing BibRef

Yan, W.J.[Wen-Jing], Ruan, Q.N.[Qian-Nan], Fu, X.L.[Xiao-Lan], Sun, Y.Q.[Yu-Qi],
Perceived emotions and AU combinations in ambiguous facial expressions,
PRL(164), 2022, pp. 74-80.
Elsevier DOI 2212
Ambiguous facial expressions, Perceived emotion, Action unit (AU), Network analysis BibRef

Tan, X.H.[Xiao-Hui], Fan, Y.[Yachun], Sun, M.[Mingrui], Zhuang, M.[Meiqi], Qu, F.[Fangbing],
An emotion index estimation based on facial action unit prediction,
PRL(164), 2022, pp. 183-190.
Elsevier DOI 2212
Affective computing, Emotion index estimation, Facial action units prediction, Convolutional neutral network BibRef

Deng, J.[Jiawen], Ren, F.[Fuji],
Multi-Label Emotion Detection via Emotion-Specified Feature Extraction and Emotion Correlation Learning,
AffCom(14), No. 1, January 2023, pp. 475-486.
IEEE DOI 2303
Correlation, Feature extraction, Task analysis, Sentiment analysis, Emotion recognition, Context modeling, Multi-label, multi-label focal loss BibRef

Xu, Z.W.[Zhi-Wei], Wang, S.F.[Shang-Fei],
Emotional Attention Detection and Correlation Exploration for Image Emotion Distribution Learning,
AffCom(14), No. 1, January 2023, pp. 357-369.
IEEE DOI 2303
Feature extraction, Visualization, Semantics, Mathematical model, Task analysis, Prediction algorithms, Correlation, graph convolutional network BibRef

Karumbaiah, S.[Shamya], Baker, R.S.[Ryan S.], Ocumpaugh, J.[Jaclyn], Andres, J.M.A.L.[Juliana Ma. Alexandra L.],
A Re-Analysis and Synthesis of Data on Affect Dynamics in Learning,
AffCom(14), No. 2, April 2023, pp. 1696-1710.
IEEE DOI 2306
Context modeling, Predictive models, Urban areas, Analytical models, Statistics, Sociology, Affective computing, modeling human emotion BibRef

Bisogni, C.[Carmen], Cimmino, L.[Lucia], de Marsico, M.[Maria], Hao, F.[Fei], Narducci, F.[Fabio],
Emotion recognition at a distance: The robustness of machine learning based on hand-crafted facial features vs deep learning models,
IVC(136), 2023, pp. 104724.
Elsevier DOI 2308
Emotion recognition, Facial expression, Expression recognition at a distance, Deep learning, Mediapipe BibRef

Zhang, T.Y.[Tian-Yi], El Ali, A.[Abdallah], Wang, C.[Chen], Hanjalic, A.[Alan], Cesar, P.[Pablo],
Weakly-Supervised Learning for Fine-Grained Emotion Recognition Using Physiological Signals,
AffCom(14), No. 3, July 2023, pp. 2304-2322.
IEEE DOI 2310
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Zhang, T.Y.[Tian-Yi], El Ali, A.[Abdallah], Hanjalic, A.[Alan], Cesar, P.[Pablo],
Few-Shot Learning for Fine-Grained Emotion Recognition Using Physiological Signals,
MultMed(25), 2023, pp. 3773-3787.
IEEE DOI 2310
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Bota, P.[Patrícia], Zhang, T.Y.[Tian-Yi], El Ali, A.[Abdallah], Fred, A.[Ana], da Silva, H.P.[Hugo Plácido], Cesar, P.[Pablo],
Group Synchrony for Emotion Recognition Using Physiological Signals,
AffCom(14), No. 4, October 2023, pp. 2614-2625.
IEEE DOI 2312
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Pei, E.[Ercheng], Zhao, Y.[Yong], Oveneke, M.C.[Meshia Cédric], Jiang, D.M.[Dong-Mei], Sahli, H.[Hichem],
A Bayesian Filtering Framework for Continuous Affect Recognition From Facial Images,
MultMed(25), 2023, pp. 3709-3722.
IEEE DOI 2310
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Liao, J.C.[Jia-Cheng], Hao, Y.[Yan], Zhou, Z.Y.[Zhuo-Yi], Pan, J.H.[Jia-Hui], Liang, Y.[Yan],
Sequence-level affective level estimation based on pyramidal facial expression features,
PR(145), 2024, pp. 109958.
Elsevier DOI 2311
Sequence-level affective level estimation, Facial expression features pyramid network, Temporal transformer encoder BibRef

Li, J.L.[Jeng-Lin], Lee, C.C.[Chi-Chun],
An Enroll-to-Verify Approach for Cross-Task Unseen Emotion Class Recognition,
AffCom(14), No. 4, October 2023, pp. 3066-3077.
IEEE DOI 2312
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Somarathna, R.[Rukshani], Bednarz, T.[Tomasz], Mohammadi, G.[Gelareh],
Virtual Reality for Emotion Elicitation: A Review,
AffCom(14), No. 4, October 2023, pp. 2626-2645.
IEEE DOI 2312
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Yang, K.[Kangning], Tag, B.[Benjamin], Wang, C.F.[Chao-Fan], Gu, Y.[Yue], Sarsenbayeva, Z.[Zhanna], Dingler, T.[Tilman], Wadley, G.[Greg], Goncalves, J.[Jorge],
Survey on Emotion Sensing Using Mobile Devices,
AffCom(14), No. 4, October 2023, pp. 2678-2696.
IEEE DOI 2312
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Yang, K.[Kailai], Zhang, T.[Tianlin], Alhuzali, H.[Hassan], Ananiadou, S.[Sophia],
Cluster-Level Contrastive Learning for Emotion Recognition in Conversations,
AffCom(14), No. 4, October 2023, pp. 3269-3280.
IEEE DOI Code:
WWW Link. 2312
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Deng, S.[Sinuo], Wu, L.F.[Li-Fang], Shi, G.[Ge], Xing, L.[Lehao], Hu, W.J.[Wen-Jin], Zhang, H.[Heng], Xiang, Y.[Ye],
Simple But Powerful, a Language-Supervised Method for Image Emotion Classification,
AffCom(14), No. 4, October 2023, pp. 3317-3331.
IEEE DOI 2312
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Wang, Z.Y.[Zhe-Yu], Zheng, J.Y.[Jie-Ying], Liu, F.[Feng],
Improvement of continuous emotion recognition of temporal convolutional networks with incomplete labels,
IET-IPR(18), No. 4, 2024, pp. 914-925.
DOI Link 2403
convolutional neural nets, emotion recognition BibRef

Bisogni, C.[Carmen], Cascone, L.[Lucia], Nappi, M.[Michele], Pero, C.[Chiara],
POSER: POsed vs Spontaneous Emotion Recognition using fractal encoding,
IVC(144), 2024, pp. 104952.
Elsevier DOI 2404
Emotion recognition, Face recognition, Partitioned iterated function systems, Fractal encoding, Spontaneous emotions BibRef

Zhang, X.Q.[Xiao-Qin], Li, M.[Min], Lin, S.[Sheng], Xu, H.[Hang], Xiao, G.[Guobao],
Transformer-Based Multimodal Emotional Perception for Dynamic Facial Expression Recognition in the Wild,
CirSysVideo(34), No. 5, May 2024, pp. 3192-3203.
IEEE DOI 2405
Feature extraction, Transformers, Face recognition, Emotion recognition, Visualization, Data mining, deep learning BibRef


Yang, J.Y.[Jing-Yuan], Huang, Q.[Qirui], Ding, T.T.[Ting-Ting], Lischinski, D.[Dani], Cohen-Or, D.[Daniel], Huang, H.[Hui],
EmoSet: A Large-scale Visual Emotion Dataset with Rich Attributes,
ICCV23(20326-20337)
IEEE DOI Code:
WWW Link. 2401
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de Carolis, B.[Berardina], Macchiarulo, N.[Nicola], Palestra, G.[Giuseppe], de Matteis, A.P.[Alberto Pio], Lippolis, A.[Andrea],
Fermouth: Facial Emotion Recognition from the Mouth Region,
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Achlioptas, P.[Panos], Ovsjanikov, M.[Maks], Guibas, L.J.[Leonidas J.], Tulyakov, S.[Sergey],
Affection: Learning Affective Explanations for Real-World Visual Data,
CVPR23(6641-6651)
IEEE DOI 2309
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Xue, F.[Fanglei], Sun, Y.F.[Yi-Fan], Yang, Y.[Yi],
Exploring Expression-related Self-supervised Learning and Spatial Reserve Pooling for Affective Behaviour Analysis,
ABAW23(5701-5708)
IEEE DOI 2309
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Zhang, S.[Su], Zhao, Z.Y.[Zi-Yuan], Guan, C.T.[Cun-Tai],
Multimodal Continuous Emotion Recognition: A Technical Report for ABAW5,
ABAW23(5764-5769)
IEEE DOI 2309
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de Lima-Costa, W.[Willams], Martínez, E.T.[Estefania Talavera], Figueiredo, L.S.[Lucas Silva], Teichrieb, V.[Veronica],
High-level context representation for emotion recognition in images,
LXCV23(326-334)
IEEE DOI 2309
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Yang, D.[Dingkang], Chen, Z.Y.[Zhao-Yu], Wang, Y.Z.[Yu-Zheng], Wang, S.[Shunli], Li, M.C.[Ming-Cheng], Liu, S.[Siao], Zhao, X.[Xiao], Huang, S.[Shuai], Dong, Z.[Zhiyan], Zhai, P.[Peng], Zhang, L.H.[Li-Hua],
Context De-Confounded Emotion Recognition,
CVPR23(19005-19015)
IEEE DOI 2309
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Yu, J.[Jun], Zhu, J.[Jichao], Zhu, W.Y.[Wang-Yuan], Cai, Z.[Zhongpeng], Xie, G.[Guochen], Li, R.[Renda], Zhao, G.[Gongpeng], Ling, Q.[Qiang], Wang, L.[Lei], Wang, C.[Cong], Qiu, L.[Luyu], Zheng, W.[Wei],
A Dual Branch Network for Emotional Reaction Intensity Estimation,
ABAW23(5811-5818)
IEEE DOI 2309
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Qiu, F.[Feng], Ma, B.[Bowen], Zhang, W.[Wei], Ding, Y.[Yu],
Multi-modal Emotion Reaction Intensity Estimation with Temporal Augmentation,
ABAW23(5777-5784)
IEEE DOI 2309
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Li, J.[Jia], Chen, Y.[Yin], Zhang, X.S.[Xue-Song], Nie, J.T.[Jian-Tao], Li, Z.Q.[Zi-Qiang], Yu, Y.C.[Yang-Chen], Zhang, Y.[Yan], Hong, R.C.[Ri-Chang], Wang, M.[Meng],
Multimodal Feature Extraction and Fusion for Emotional Reaction Intensity Estimation and Expression Classification in Videos with Transformers,
ABAW23(5838-5844)
IEEE DOI 2309
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Fang, Y.[Yini], Wu, L.[Liang], Jumelle, F.[Frederic], Shi, B.[Bertram],
Integrating Holistic and Local Information to Estimate Emotional Reaction Intensity,
ABAW23(5934-5939)
IEEE DOI 2309
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Aslam, M.H.[Muhammad Haseeb], Zeeshan, M.O.[Muhammad Osama], Pedersoli, M.[Marco], Koerich, A.L.[Alessandro L.], Bacon, S.[Simon], Granger, E.[Eric],
Privileged Knowledge Distillation for Dimensional Emotion Recognition in the Wild,
FGAHI23(3338-3347)
IEEE DOI 2309
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Lee, B.[Bokyeung], Shin, H.[Hyunuk], Ku, B.[Bonhwa], Ko, H.S.[Han-Seok],
Frame Level Emotion Guided Dynamic Facial Expression Recognition with Emotion Grouping,
ABAW23(5681-5691)
IEEE DOI 2309
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Kollias, D.[Dimitrios],
ABAW: Learning from Synthetic Data & Multi-task Learning Challenges,
ABAWE22(157-172).
Springer DOI 2304
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Sun, H.Y.[Hai-Yang], Lian, Z.[Zheng], Liu, B.[Bin], Tao, J.H.[Jian-Hua], Sun, L.[Licai], Cai, C.[Cong], He, Y.[Yu],
Two-aspect Information Interaction Model for ABAW4 Multi-task Challenge,
ABAWE22(173-180).
Springer DOI 2304
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Li, Y.F.[Yi-Fan], Sun, H.[Haomiao], Liu, Z.[Zhaori], Han, H.[Hu], Shan, S.G.[Shi-Guang],
Affective Behaviour Analysis Using Pretrained Model with Facial Prior,
ABAWE22(19-30).
Springer DOI 2304
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Zhang, T.G.[Teng-Gan], Liu, C.H.[Chuan-He], Liu, X.L.[Xiao-Long], Liu, Y.C.[Yu-Chen], Meng, L.[Liyu], Sun, L.[Lei], Jiang, W.Q.[Wen-Qiang], Zhang, F.Y.[Feng-Yuan], Zhao, J.M.[Jin-Ming], Jin, Q.[Qin],
Multi-task Learning Framework for Emotion Recognition In-the-wild,
ABAWE22(143-156).
Springer DOI 2304
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Mittel, A.[Akshita], Tripathi, S.[Shashank],
Peri: Part Aware Emotion Recognition in the Wild,
ABAWE22(76-92).
Springer DOI 2304
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Lee, H.[Hyungjun], Lim, H.[Hwangyu], Lim, S.[Sejoon],
Byel: Bootstrap Your Emotion Latent,
ABAWE22(121-131).
Springer DOI 2304
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Savchenko, A.V.[Andrey V.],
MT-emotieffnet for Multi-task Human Affective Behavior Analysis and Learning from Synthetic Data,
ABAWE22(45-59).
Springer DOI 2304
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Gera, D.[Darshan], Kumar, B.V.R.[Bobbili Veerendra Raj], Badveeti, N.S.K.[Naveen Siva Kumar], Balasubramanian, S.,
Facial Affect Recognition Using Semi-supervised Learning with Adaptive Threshold,
ABAWE22(31-44).
Springer DOI 2304
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Shahabinejad, M.[Mostafa], Wang, Y.[Yang], Yu, Y.H.[Yuan-Hao], Tang, J.[Jin], Li, J.[Jiani],
Toward Personalized Emotion Recognition: A Face Recognition Based Attention Method for Facial Emotion Recognition,
FG21(1-5)
IEEE DOI 2303
Emotion recognition, Face recognition, Gesture recognition, Convolutional neural networks, Task analysis BibRef

Pikoulis, I.[Ioannis], Filntisis, P.P.[Panagiotis P.], Maragos, P.[Petros],
Leveraging Semantic Scene Characteristics and Multi-Stream Convolutional Architectures in a Contextual Approach for Video-Based Visual Emotion Recognition in the Wild,
FG21(01-08)
IEEE DOI 2303
Emotion recognition, Visualization, Motion segmentation, Semantics, Lighting, Gesture recognition, Feature extraction BibRef

Madapana, N.[Naveen], Wachs, J.[Juan],
ZF-SSE: A Unified Sequential Semantic Encoder for Zero-Few-Shot Learning,
FG21(1-8)
IEEE DOI 2303
Learning systems, Emotion recognition, Face recognition, Semantics, Gesture recognition, Object recognition BibRef

Jegorova, M.[Marija], Petridis, S.[Stavros], Pantic, M.[Maja],
SS-VAERR: Self-Supervised Apparent Emotional Reaction Recognition from Video,
FG23(1-8)
IEEE DOI 2303
Emotion recognition, Annotations, Face recognition, Self-supervised learning, Gesture recognition, Task analysis BibRef

Jia, G.[Guoli], Yang, J.F.[Ju-Feng],
S2-VER: Semi-supervised Visual Emotion Recognition,
ECCV22(XXXVII:493-509).
Springer DOI 2211
BibRef

Yang, D.K.[Ding-Kang], Huang, S.[Shuai], Wang, S.L.[Shun-Li], Liu, Y.[Yang], Zhai, P.[Peng], Su, L.Z.[Liu-Zhen], Li, M.C.[Ming-Cheng], Zhang, L.H.[Li-Hua],
Emotion Recognition for Multiple Context Awareness,
ECCV22(XXXVII:144-162).
Springer DOI 2211
BibRef

Kim, D.[Daeha], Song, B.C.[Byung Cheol],
Emotion-aware Multi-view Contrastive Learning for Facial Emotion Recognition,
ECCV22(XIII:178-195).
Springer DOI 2211
BibRef

Bishay, M.[Mina], Turcot, J.[Jay], Page, G.[Graham], Mavadati, M.[Mohammad],
Automatic Detection of Sentimentality from Facial Expressions,
ICIP22(321-325)
IEEE DOI 2211
Training, Measurement, Gold, Emotion recognition, Multilayer perceptrons, Feature extraction, Sentimentality, Ad-level KPIs BibRef

Meng, L.[Liyu], Liu, Y.C.[Yu-Chen], Liu, X.L.[Xiao-Long], Huang, Z.P.[Zhao-Pei], Jiang, W.Q.[Wen-Qiang], Zhang, T.G.[Teng-Gan], Liu, C.[Chuanhe], Jin, Q.[Qin],
Valence and Arousal Estimation based on Multimodal Temporal-Aware Features for Videos in the Wild,
ABAW22(2344-2351)
IEEE DOI 2210
Correlation coefficient, Visualization, Smoothing methods, Fuses, Estimation, Predictive models, Transformers BibRef

Surabhi, S.[Saimourya], Shah, B.[Bhavik], Washington, P.[Peter], Mutlu, O.C.[Onur Cezmi], Leblanc, E.[Emilie], Mohite, P.[Prathamesh], Husic, A.[Arman], Kline, A.[Aaron], Dunlap, K.[Kaitlyn], McNealis, M.[Maya], Liu, B.[Bennett], Deveaux, N.[Nick], Sleiman, E.[Essam], Wall, D.P.[Dennis P.],
TikTok for good: Creating a diverse emotion expression database,
ABAW22(2495-2505)
IEEE DOI 2210
Bridges, Emotion recognition, Databases, Social networking (online), Face recognition BibRef

Deng, D.[Didan], Shi, B.E.[Bertram E.],
Estimating Multiple Emotion Descriptors by Separating Description and Inference,
ABAW22(2391-2399)
IEEE DOI 2210
Space vehicles, Representation learning, Visualization, Emotion recognition, Gold, Face recognition, Psychology BibRef

Stratton, D.[Derek], Hand, E.[Emily],
Bridging the Gap Between Automated and Human Facial Emotion Perception,
ABAW22(2400-2410)
IEEE DOI 2210
Emotion recognition, Uncertainty, Sociology, Psychology, Natural language processing BibRef

Ouzar, Y.[Yassine], Bousefsaf, F.[Frédéric], Djeldjli, D.[Djamaleddine], Maaoui, C.[Choubeila],
Video-based multimodal spontaneous emotion recognition using facial expressions and physiological signals,
ABAW22(2459-2468)
IEEE DOI 2210
Emotion recognition, Face recognition, Photoplethysmography, Feature extraction, Physiology, Spatiotemporal phenomena BibRef

Xu, L.W.[Li-Wen], Wang, Z.T.[Zheng-Tao], Wu, B.[Bin], Lui, S.[Simon],
MDAN: Multi-level Dependent Attention Network for Visual Emotion Analysis,
CVPR22(9469-9478)
IEEE DOI 2210
Bridges, Visualization, Correlation, Computational modeling, Semantics, Benchmark testing, Recognition: detection, retrieval BibRef

Pereira, L.[Lara], Brás, S.[Susana], Sebastiăo, R.[Raquel],
Characterization of Emotions Through Facial Electromyogram Signals,
IbPRIA22(230-241).
Springer DOI 2205
BibRef

Jia, M.L.[Meng-Lin], Wu, Z.[Zuxuan], Reiter, A.[Austin], Cardie, C.[Claire], Belongie, S.[Serge], Lim, S.N.[Ser-Nam],
Exploring Visual Engagement Signals for Representation Learning,
ICCV21(4186-4197)
IEEE DOI 2203
Representation learning, Visualization, Emotion recognition, Social networking (online), Computational modeling, Vision + language BibRef

Vonikakis, V.[Vassilios], Dexter, N.Y.R.[Neo Yuan Rong], Winkler, S.[Stefan],
Morphset: Augmenting Categorical Emotion Datasets With Dimensional Affect Labels Using Face Morphing,
ICIP21(2713-2717)
IEEE DOI 2201
Emotion recognition, Annotations, Face recognition, Image processing, Computational modeling, Supervised learning BibRef

Sanchez, E.[Enrique], Tellamekala, M.K.[Mani Kumar], Valstar, M.[Michel], Tzimiropoulos, G.[Georgios],
Affective Processes: stochastic modelling of temporal context for emotion and facial expression recognition,
CVPR21(9070-9080)
IEEE DOI 2111
Emotion recognition, Uncertainty, Face recognition, Supervised learning, Stochastic processes, Estimation, Predictive models BibRef

Yang, J.Y.[Jing-Yuan], Li, J.[Jie], Li, L.[Leida], Wang, X.M.[Xiu-Mei], Gao, X.B.[Xin-Bo],
A Circular-Structured Representation for Visual Emotion Distribution Learning,
CVPR21(4235-4244)
IEEE DOI 2111
Visualization, Social networking (online), Psychology, Pattern recognition, Task analysis BibRef

d'Apolito, S.[Stefano], Paudel, D.P.[Danda Pani], Huang, Z.W.[Zhi-Wu], Romero, A.[Andrés], Van Gool, L.J.[Luc J.],
GANmut: Learning Interpretable Conditional Space for Gamut of Emotions,
CVPR21(568-577)
IEEE DOI 2111
Training, Image synthesis, Computational modeling, Aerospace electronics, Search problems, Pattern recognition BibRef

González-Meneses, Y.N.[Yesenia N.], Guerrero-García, J.[Josefina], Reyes-García, C.A.[Carlos Alberto], Zatarain-Cabada, R.[Ramón],
Automatic Recognition of Learning-Centered Emotions,
MCPR21(33-43).
Springer DOI 2108
BibRef

Zhang, S.W.[Si-Wei], Huang, Z.W.[Zhi-Wu], Paudel, D.P.[Danda Pani], Van Gool, L.J.[Luc J.],
Facial Emotion Recognition with Noisy Multi-task Annotations,
WACV21(21-31)
IEEE DOI 2106
Emotion recognition, Correlation, Annotations, Games, Encoding BibRef

Diamantini, C.[Claudia], Mircoli, A.[Alex], Potena, D.[Domenico], Storti, E.[Emanuele],
Automatic Annotation of Corpora For Emotion Recognition Through Facial Expressions Analysis,
ICPR21(5650-5657)
IEEE DOI 2105
Emotion recognition, Sentiment analysis, Gold, Machine learning algorithms, Annotations, dataset for sentiment analysis BibRef

Kolling, C.[Camila], Araujo, V.[Victor], Barros, R.C.[Rodrigo C.], Musse, S.R.[Soraia Raupp],
How Does Computer Animation Affect Our Perception of Emotions in Video Summarization?,
ISVC20(II:374-385).
Springer DOI 2103
BibRef

Shehu, H.A.[Harisu Abdullahi], Browne, W.[Will], Eisenbarth, H.[Hedwig],
Emotion Categorization from Video-frame Images Using a Novel Sequential Voting Technique,
ISVC20(II:618-632).
Springer DOI 2103
BibRef

Savchenko, A.V.[Andrey V.],
Video-based Frame-level Facial Analysis of Affective Behavior on Mobile Devices using EfficientNets,
ABAW22(2358-2365)
IEEE DOI 2210
Emotion recognition, Analytical models, Computational modeling, Multitasking, Feature extraction, Real-time systems, Mobile handsets BibRef

Demochkina, P.[Polina], Savchenko, A.V.[Andrey V.],
Mobileemotiface: Efficient Facial Image Representations in Video-based Emotion Recognition on Mobile Devices,
IMTA20(266-274).
Springer DOI 2103
BibRef

Haddad, J.[Jad], Lezoray, O.[Olivier], Hamel, P.[Philippe],
3D-CNN for Facial Emotion Recognition in Videos,
ISVC20(II:298-309).
Springer DOI 2103
BibRef

Kota, V., Gali, G.M., Nwogu, I.,
A Computational View of the Emotional Regulation of Disgust using Multimodal Sensors,
FG20(567-571)
IEEE DOI 2102
biomechanics, cognition, electrocardiography, electromyography, emotion recognition, face recognition, medical signal processing, disgust emotion BibRef

Happy, S., Dantcheva, A., Bremond, F.,
Semi-supervised Emotion Recognition using Inconsistently Annotated Data,
FG20(286-293)
IEEE DOI 2102
Data models, Adaptation models, Training, Predictive models, Noise measurement, Face recognition, Emotion recognition BibRef

Zhang, Z., Yi, M., Xu, J., Zhang, R., Shen, J.,
Two-stage Recognition and Beyond for Compound Facial Emotion Recognition,
FG20(900-904)
IEEE DOI 2102
Gesture recognition, Face recognition, emotion recognition BibRef

Luo, Z., Zhang, Z.,
Challenge report: Compound Emotion challenge,
FG20(905-907)
IEEE DOI 2102
Training, Gesture recognition, Face recognition BibRef

Viegas, C.,
Two Stage Emotion Recognition using Frame-level and Video-level Features,
FG20(912-915)
IEEE DOI 2102
Support vector machines, Radio frequency, Feature extraction, Emotion recognition, Training, emotion recognition BibRef

Deng, D., Chen, Z., Shi, B.E.,
Multitask Emotion Recognition with Incomplete Labels,
FG20(592-599)
IEEE DOI 2102
Task analysis, Gold, Estimation, Training, Emotion recognition, Feature extraction, Correlation, Emotion Recognition, Incomplete Label BibRef

Happy, S.L., Dantcheva, A., Das, A., Bremond, F., Zeghari, R., Robert, P.,
Apathy Classification by Exploiting Task Relatedness,
FG20(489-494)
IEEE DOI 2102
Task analysis, Videos, Face recognition, Histograms, Feature extraction, Emotional responses, Visualization, task relatedness BibRef

Liu, J., Foged, I.W., Moeslund, T.B.,
Vision-based Individual Factors Acquisition for Thermal Comfort Assessment in a Built Environment,
FG20(662-666)
IEEE DOI 2102
Videos, Temperature measurement, Training, Optical imaging, Skin, HVAC, Thermometers BibRef

Kollias, D., Schulc, A., Hajiyev, E., Zafeiriou, S.,
Analysing Affective Behavior in the First ABAW 2020 Competition,
FG20(637-643)
IEEE DOI 2102
Videos, Annotations, Gold, Databases, Training, Task analysis, Face recognition, valence, arousal, basic expressions, action units, mobilenet BibRef

Kuhnke, F., Rumberg, L., Ostermann, J.[Jörn],
Two-Stream Aural-Visual Affect Analysis in the Wild,
FG20(600-605)
IEEE DOI 2102
Videos, Training, Task analysis, Visualization, Streaming media, Face recognition, expression recognition, action units, emotion recognition BibRef

Lei, S., Stefanov, K., Gratch, J.,
Emotion or expressivity? An automated analysis of nonverbal perception in a social dilemma,
FG20(544-551)
IEEE DOI 2102
Videos, Observers, Face recognition, Games, Tools, Standards, Protocols BibRef

Li, B.H.[Bing-Hua], Li, C.[Chao], Duan, F.[Feng], Zheng, N.[Ning], Zhao, Q.B.[Qi-Bin],
TPFN: Applying Outer Product Along Time to Multimodal Sentiment Analysis Fusion on Incomplete Data,
ECCV20(XXIV:431-447).
Springer DOI 2012
BibRef

Lim, L., Khor, H.Q., Chaemchoy, P., See, J., Wong, L.K.,
Where Is The Emotion? Dissecting A Multi-Gap Network For Image Emotion Classification,
ICIP20(1886-1890)
IEEE DOI 2011
Feature extraction, Visualization, Neural networks, Streaming media, Emotion recognition, Psychology, Robustness, class activation maps BibRef

Chouhayebi, H., Riffi, J., Mahraz, M.A., Yahyaouy, A., Tairi, H., Alioua, N.,
Facial expression recognition based on geometric features,
ISCV20(1-6)
IEEE DOI 2011
emotion recognition, face recognition, feature extraction, image classification, support vector machines, diverse emotions, SVM BibRef

Kossaifi, J., Toisoul, A., Bulat, A., Panagakis, Y., Hospedales, T.M., Pantic, M.,
Factorized Higher-Order CNNs With an Application to Spatio-Temporal Emotion Estimation,
CVPR20(6059-6068)
IEEE DOI 2008
Tensile stress, Kernel, Estimation, Training, Videos, Neural networks BibRef

Wei, Z., Zhang, J., Lin, Z., Lee, J., Balasubramanian, N., Hoai, M., Samaras, D.,
Learning Visual Emotion Representations From Web Data,
CVPR20(13103-13112)
IEEE DOI 2008
Visualization, Feature extraction, Emotion recognition, Task analysis, Taxonomy, Training, Noise measurement BibRef

Zhan, C., She, D., Zhao, S., Cheng, M., Yang, J.,
Zero-Shot Emotion Recognition via Affective Structural Embedding,
ICCV19(1151-1160)
IEEE DOI 2004
emotion recognition, feature extraction, learning (artificial intelligence), psychology, BibRef

Zheng, R.L.[Ruo-Lin], Li, W.X.[Wei-Xin], Wang, Y.H.[Yun-Hong],
Visual Sentiment Analysis by Leveraging Local Regions and Human Faces,
MMMod20(I:303-314).
Springer DOI 2003
BibRef

Mo, S.[Siyi], Yang, W.M.[Wen-Ming], Wang, G.J.[Gui-Jin], Liao, Q.M.[Qing-Min],
Emotion Recognition with Facial Landmark Heatmaps,
MMMod20(I:278-289).
Springer DOI 2003
BibRef

Jia, X.[Xiuyi], Zheng, X.[Xiang], Li, W.W.[Wei-Wei], Zhang, C.Q.[Chang-Qing], Li, Z.C.[Ze-Chao],
Facial Emotion Distribution Learning by Exploiting Low-Rank Label Correlations Locally,
CVPR19(9833-9842).
IEEE DOI 2002
BibRef

Moroto, Y., Maeda, K., Ogawa, T., Haseyama, M.,
Estimation of Emotion Labels via Tensor-Based Spatiotemporal Visual Attention Analysis,
ICIP19(4105-4109)
IEEE DOI 1910
Emotion estimation, eye gaze, spatiotemporal visual attention analysis, tensor analysis BibRef

Li, Y.Y.[Yan-Ying], Cheng, H.J.[Hsin-Jung], Liu, Y.[Yen], Shen, C.T.[Chih-Tsung],
Edge-Computing Convolutional Neural Network with Homography-Augmented Data for Facial Emotion Recognition,
ICIP19(3287-3291)
IEEE DOI 1910
Face Recognition, Convolutional Neural Network, ASIC, VPU BibRef

Wang, C., Zeng, J., Shan, S., Chen, X.,
Multi-Task Learning of Emotion Recognition and Facial Action Unit Detection with Adaptively Weights Sharing Network,
ICIP19(56-60)
IEEE DOI 1910
facial expression recognition, emotion classification, facial action unit detection, multi-task learning BibRef

Pandey, R.K.[Ram Krishna], Karmakar, S.[Souvik], Ramakrishnan, A.G., Saha, N.,
Improving Facial Emotion Recognition Systems with Crucial Feature Extractors,
CIAP19(I:268-279).
Springer DOI 1909
BibRef

Aminbeidokhti, M.[Masih], Pedersoli, M.[Marco], Cardinal, P.[Patrick], Granger, E.[Eric],
Emotion Recognition with Spatial Attention and Temporal Softmax Pooling,
ICIAR19(I:323-331).
Springer DOI 1909
BibRef

Aly, S.F.[Sherin F.], Abbott, A.L.[A. Lynn],
Facial Emotion Recognition with Varying Poses and/or Partial Occlusion Using Multi-stage Progressive Transfer Learning,
SCIA19(101-112).
Springer DOI 1906
BibRef

Zhu, X.L.[Xue-Lin], Cao, B.W.[Bi-Wei], Xu, S.[Shuai], Liu, B.[Bo], Cao, J.X.[Jiu-Xin],
Joint Visual-Textual Sentiment Analysis Based on Cross-Modality Attention Mechanism,
MMMod19(I:264-276).
Springer DOI 1901
BibRef

Gonzalez-Diaz, R.[Rocio], Paluzo-Hidalgo, E.[Eduardo], Quesada, J.F.[José F.],
Towards Emotion Recognition: A Persistent Entropy Application,
CTIC19(96-109).
Springer DOI 1901
BibRef

Nguyen, D., Nguyen, K., Sridharan, S., Abbasnejad, I., Dean, D., Fookes, C.,
Meta Transfer Learning for Facial Emotion Recognition,
ICPR18(3543-3548)
IEEE DOI 1812
Task analysis, Emotion recognition, Face recognition, Feature extraction, Face, Computer architecture BibRef

Kumar, R.K., Garain, J., Kisku, D.R., Sanyal, G.,
Estimating Attention of Faces Due to its Growing Level of Emotions,
Cognitive18(2033-20338)
IEEE DOI 1812
Feature extraction, Training, Databases, Task analysis, Visualization, Convolution, Testing BibRef

Xu, J., Dong, Y., Ma, L., Bai, H.,
Video-based Emotion Recognition using Aggregated Features and Spatio-temporal Information,
ICPR18(2833-2838)
IEEE DOI 1812
Feature extraction, Videos, Emotion recognition, Task analysis, Face recognition, Face BibRef

Tautkute, I., Trzcinski, T., Bielski, A.,
I Know How You Feel: Emotion Recognition with Facial Landmarks,
WiCV18(1959-19592)
IEEE DOI 1812
Emotion recognition, Task analysis, Face, Face recognition, Convolutional neural networks, Databases BibRef

Yagis, E.[Ekin], Unel, M.[Mustafa],
Facial Expression Based Emotion Recognition Using Neural Networks,
ICIAR18(210-217).
Springer DOI 1807
BibRef

Abuhammad, H.[Huthaifa], Everson, R.[Richard],
Emotional Faces in the Wild: Feature Descriptors for Emotion Classification,
ICIAR18(164-174).
Springer DOI 1807
BibRef

Torres-Valencia, C., Alvarez-Meza, A., Orozco-Gutierrez, A.,
Emotion Assessment Using Adaptive Learning-Based Relevance Analysis,
ICIAR18(193-200).
Springer DOI 1807
BibRef

Gaus, Y.F.A., Meng, H.,
Linear and Non-Linear Multimodal Fusion for Continuous Affect Estimation In-the-Wild,
FG18(492-498)
IEEE DOI 1806
Correlation, Emotion recognition, Estimation, Feature extraction, Linear regression, Mathematical model, Predictive models, affect, non-linear BibRef

Sokolov, D., Patkin, M.,
Real-Time Emotion Recognition on Mobile Devices,
FG18(787-787)
IEEE DOI 1806
Emotion recognition, Face recognition, Feature extraction, Machine learning, Mobile handsets, Neural networks, mobile devices BibRef

Shamsi, S.N., Singh, B.P., Wadhwa, M.,
Group Affect Prediction Using Multimodal Distributions,
Assist18(77-83)
IEEE DOI 1806
convolution, emotion recognition, feature extraction, feedforward neural nets, object detection, CNN model, Training BibRef

Kowalski, M., Nasarzewski, Z., Galinski, G., Garbat, P.,
HoloFace: Augmenting Human-to-Human Interactions on HoloLens,
WACV18(141-149)
IEEE DOI 1806
emotion recognition, face recognition, pose estimation, solid modelling, HoloFace framework, HoloLens user, BibRef

Knyazev, B., Shvetsov, R., Efremova, N., Kuharenko, A.,
Leveraging Large Face Recognition Data for Emotion Classification,
FG18(692-696)
IEEE DOI 1806
Emotion recognition, Face, Face recognition, Support vector machines, Task analysis, Training, Videos, video processing BibRef

Lai, Y.H., Lai, S.H.,
Emotion-Preserving Representation Learning via Generative Adversarial Network for Multi-View Facial Expression Recognition,
FG18(263-270)
IEEE DOI 1806
Emotion recognition, Face, Face recognition, Feature extraction, Generators, face frontalization, pose variation BibRef

Loob, C.[Christer], Rasti, P.[Pejman], Lüsi, I.[Iiris], Jacques Junior, J.C.S.[Julio C.S.], Baró, X.[Xavier], Escalera, S.[Sergio], Sapinski, T.[Tomasz], Kaminska, D.[Dorota], Anbarjafari, G.[Gholamreza],
Dominant and Complementary Multi-Emotional Facial Expression Recognition Using C-Support Vector Classification,
FG17(833-838)
IEEE DOI 1707
Databases, Emotion recognition, Face, Face recognition, Feature extraction, Kernel, Support vector machines BibRef

Kim, Y.G., Huynh, X.P.,
Discrimination Between Genuine Versus Fake Emotion Using Long-Short Term Memory with Parametric Bias and Facial Landmarks,
EmotionComp17(3065-3072)
IEEE DOI 1802
Boosting, Emotion recognition, Face, Face recognition, Mirrors, Neurons, Training BibRef

Saxen, F., Werner, P., Al-Hamadi, A.,
Real vs. Fake Emotion Challenge: Learning to Rank Authenticity from Facial Activity Descriptors,
EmotionComp17(3073-3078)
IEEE DOI 1802
Computational modeling, Estimation, Gold, Support vector machines, Training, Videos BibRef

Li, L., Baltrusaitis, T., Sun, B., Morency, L.P.,
Combining Sequential Geometry and Texture Features for Distinguishing Genuine and Deceptive Emotions,
EmotionComp17(3147-3153)
IEEE DOI 1802
Emotion recognition, Face, Image reconstruction, Logic gates, Mathematical model, Visualization BibRef

Li, J.S.[Jian-Shu], Chen, Y.P.[Yun-Peng], Xiao, S.T.[Sheng-Tao], Zhao, J.[Jian], Roy, S.[Sujoy], Feng, J.S.[Jia-Shi], Yan, S.C.[Shui-Cheng], Sim, T.[Terence],
Estimation of Affective Level in the Wild with Multiple Memory Networks,
FaceWild17(1947-1954)
IEEE DOI 1709
Bidirectional control, Estimation, Face, Feature extraction, Neural networks, Predictive models, Training
See also Task Relation Networks. BibRef

Ruiz, A.[Adria], Martinez, O.[Oriol], Binefa, X.[Xavier], Sukno, F.M.[Federico M.],
Fusion of Valence and Arousal Annotations through Dynamic Subjective Ordinal Modelling,
FG17(331-338)
IEEE DOI 1707
Reliable ground truth. Affective computing, Context, Labeling, Observers, Training, Videos BibRef

McDuff, D.J., Soleymani, M.,
Large-scale Affective Content Analysis: Combining Media Content Features and Facial Reactions,
FG17(339-345)
IEEE DOI 1707
Encoding, Feature extraction, Media, Software, Tagging, Videos, Visualization BibRef

Talavera, E.[Estefania], Strisciuglio, N.[Nicola], Petkov, N.[Nicolai], Radeva, P.[Petia],
Sentiment Recognition in Egocentric Photostreams,
IbPRIA17(471-479).
Springer DOI 1706
BibRef

Zhao, K.[Kun], Yang, S.Q.[Si-Qi], Wiliem, A., Lovell, B.C.,
Landmark manifold: Revisiting the Riemannian manifold approach for facial emotion recognition,
ICPR16(1095-1100)
IEEE DOI 1705
Emotion recognition, Feature extraction, Kernel, Manifolds, Measurement, Shape, Support, vector, machines BibRef

Laranjeira, A.[Ana], Frazăo, X.[Xavier], Pimentel, A.[André], Ribeiro, B.[Bernardete],
How Deep Can We Rely on Emotion Recognition,
CIARP16(511-520).
Springer DOI 1703
BibRef

Niu, J.W.[Jian-Wei], Su, Y.M.[Yi-Ming], Mo, S.S.[Sha-Sha], Zhu, Z.Y.[Ze-Yu],
A Novel Affective Visualization System for Videos Based on Acoustic and Visual Features,
MMMod17(II: 15-27).
Springer DOI 1701
BibRef

Wang, G.L.[Guo-Long], Qin, Z.[Zheng], Xu, K.P.[Kai-Ping],
Recognizing Emotions Based on Human Actions in Videos,
MMMod17(II: 306-317).
Springer DOI 1701
BibRef

Mou, W., Gunes, H.[Hatice], Patras, I.,
Automatic Recognition of Emotions and Membership in Group Videos,
Affect16(1478-1486)
IEEE DOI 1612
BibRef

Benitez-Quiroz, C.F., Srinivasan, R., Martinez, A.M.,
EmotioNet: An Accurate, Real-Time Algorithm for the Automatic Annotation of a Million Facial Expressions in the Wild,
CVPR16(5562-5570)
IEEE DOI 1612
BibRef

Allaert, B.[Benjamin], Mennesson, J.[José], Bilasco, I.M.[Ioan Marius],
EmoGame: Towards a Self-Rewarding Methodology for Capturing Children Faces in an Engaging Context,
HBU16(3-14).
Springer DOI 1611
BibRef

Mennesson, J.[José], Allaert, B.[Benjamin], Bilasco, I.M.[Ioan Marius], van der Aa, N., Denis, A., Cruz-Lara, S.,
Faces and thoughts: An empathic dairy,
FG15(1-1)
IEEE DOI 1508
cameras BibRef

Peng, K.C., Sadovnik, A., Gallagher, A., Chen, T.,
Where do emotions come from? Predicting the Emotion Stimuli Map,
ICIP16(614-618)
IEEE DOI 1610
Benchmark testing BibRef

Zhang, H., Xu, M.,
Modeling temporal information using discrete fourier transform for recognizing emotions in user-generated videos,
ICIP16(629-633)
IEEE DOI 1610
Discrete Fourier transforms BibRef

Khan, R.A.[Rizwan Ahmed], Meyer, A.[Alexandre], Bouakaz, S.[Saida],
Automatic Affect Analysis: From Children to Adults,
ISVC15(II: 304-313).
Springer DOI 1601
BibRef

Ding, X.M.[Xin-Miao], Huang, L.[Lulu], Li, B.[Bing], Lang, C.Y.[Cong-Yan], Hua, Z.[Zhen], Wang, Y.L.[Yu-Ling],
A Novel Emotional Saliency Map to Model Emotional Attention Mechanism,
MMMod16(II: 197-206).
Springer DOI 1601
BibRef

Zhao, S.C.[Si-Cheng], Yao, H.X.[Hong-Xun], Jiang, X.L.[Xiao-Lei], Sun, X.S.[Xiao-Shuai],
Predicting discrete probability distribution of image emotions,
ICIP15(2459-2463)
IEEE DOI 1512
Emotion Distribution Prediction; Image Emotion; Sparse Learning BibRef

Happy, S.L., Routray, A.,
Robust facial expression classification using shape and appearance features,
ICAPR15(1-5)
IEEE DOI 1511
emotion recognition BibRef

Chen, H.C.[Hsieh-Chung], Comiter, M.Z.[Marcus Z.], Kung, H.T., McDanel, B.[Bradley],
Sparse Coding Trees with application to emotion classification,
AMFG15(77-86)
IEEE DOI 1510
Accuracy BibRef

Chen, H.[Hui], Li, J.D.[Jiang-Dong], Zhang, F.J.[Feng-Jun], Li, Y.[Yang], Wang, H.A.[Hong-An],
3D model-based continuous emotion recognition,
CVPR15(1836-1845)
IEEE DOI 1510
BibRef

Alashkar, T.[Taleb], Ben Amor, B.[Boulbaba], Berretti, S.[Stefano], Daoudi, M.[Mohamed],
Analyzing trajectories on Grassmann manifold for early emotion detection from depth videos,
FG15(1-6)
IEEE DOI 1508
emotion recognition
See also Grassmann framework for 4D facial shape analysis, A. BibRef

Save, M., Zazula, D., Munda, J., Potocnik, B.,
Semi-transparent mirror with hidden camera to assess human emotions,
FG15(1-1)
IEEE DOI 1508
emotion recognition BibRef

Chen, J.X.[Ji-Xu], Chang, M.C.[Ming-Ching], Tu, P.,
A live video analytic system for affect analysis in public space,
FG15(1-1)
IEEE DOI 1508
emotion recognition BibRef

Vieriu, R.L.[Radu-Laurentiu], Tulyakov, S.[Sergey], Semeniuta, S., Sangineto, E., Sebe, N.,
Facial expression recognition under a wide range of head poses,
FG15(1-7)
IEEE DOI 1508
emotion recognition BibRef

Kniaz, V.V., Smirnova, Z.N.,
Music-Elicited Emotion Identification Using Optical Flow Analysis of Human Face,
PTVSBB15(27-32).
DOI Link 1508
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Oussalah, M., Wang, S.,
Fuzzy emotion recognition model for video sequences,
IPTA12(127-132)
IEEE DOI 1503
emotion recognition BibRef

Sonmez, E.B., Sankur, B., Albayrak, S.,
Classification with emotional faces via a robust sparse classifier,
IPTA12(344-349)
IEEE DOI 1503
emotion recognition BibRef

Peng, K.C.[Kuan-Chuan], Karlsson, K.[Kolbeinn], Chen, T.H.[Tsu-Han], Zhang, D.Q.[Dong-Qing], Yu, H.[Heather],
A framework of changing image emotion using emotion prediction,
ICIP14(4637-4641)
IEEE DOI 1502
Correlation BibRef

Cardone, D.[Daniela], Merla, A.[Arcangelo],
The thermal dimension of psychophysiological and emotional responses revealed by thermal infrared imaging,
ICIP14(1942-1946)
IEEE DOI 1502
Biomedical monitoring BibRef

García, H.F.[Hernán F.], Álvarez, M.A.[Mauricio A.], Orozco, Á.Á.[Álvaro Á.],
Gaussian Process Dynamical Models for Emotion Recognition,
ISVC14(II: 799-808).
Springer DOI 1501
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Rezazadegan Tavakoli, H.[Hamed], Yanulevskaya, V.[Victoria], Rahtu, E.[Esa], Heikkila, J.[Janne], Sebe, N.[Nicu],
Emotional Valence Recognition, Analysis of Salience and Eye Movements,
ICPR14(4666-4671)
IEEE DOI 1412
Computational modeling BibRef

Lablack, A.[Adel], Danisman, T.[Taner], Bilasco, l.M.[loan Marius], Djeraba, C.[Chaabane],
A Local Approach for Negative Emotion Detection,
ICPR14(417-420)
IEEE DOI 1412
Computer vision BibRef

Ramirez, G.A.[Geovany A.], Fuentes, O.[Olac], Crites, S.L.[Stephen L.], Jimenez, M.[Maria], Ordonez, J.[Juanita],
Color Analysis of Facial Skin: Detection of Emotional State,
SocialInter14(474-479)
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Acar, E.[Esra], Hopfgartner, F.[Frank], Albayrak, S.[Sahin],
Understanding Affective Content of Music Videos through Learned Representations,
MMMod14(I: 303-314).
Springer DOI 1405
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Hadjerci, O.[Oussama], Lablack, A.[Adel], Bilasco, I.M.[Ioan Marius], Djeraba, C.[Chaabane],
Affect Recognition Using Magnitude Models of Motion,
MMMod14(II: 339-344).
Springer DOI 1405
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Huang, X.H.[Xiao-Hua], Zhao, G.Y.[Guo-Ying], Pietikainen, M.[Matti],
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BMVC13(xx-yy).
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Behrens, S.[Stephanie], Al-Hamadi, A.[Ayoub], Niese, R.[Robert], Redweik, E.[Eicke],
Automatic User-Specific Avatar Parametrisation and Emotion Mapping,
ACIVS13(192-202).
Springer DOI 1311
Classification and Recognition BibRef

Poggi, I.[Isabella], d'Errico, F.[Francesca],
Towards the Parody Machine. Qualitative Analysis and Cognitive Processes in the Parody of a Politician,
SBA13(491-500).
Springer DOI 1309
BibRef

Jeni, L.A.[László Attila], Lorincz, A.[András], Szabó, Z.[Zoltán], Cohn, J.F.[Jeffrey F.], Kanade, T.[Takeo],
Spatio-temporal Event Classification Using Time-Series Kernel Based Structured Sparsity,
ECCV14(IV: 135-150).
Springer DOI 1408
BibRef
Earlier: A2, A1, A3, A4, A5:
Emotional Expression Classification Using Time-Series Kernels,
AMFG13(889-895)
IEEE DOI 1309
3d shape BibRef

Yu, X.[Xiang], Zhang, S.T.[Shao-Ting], Yu, Y.[Yang], Dunbar, N., Jensen, M., Burgoon, J.K., Metaxas, D.N.,
Automated analysis of interactional synchrony using robust facial tracking and expression recognition,
FG13(1-6)
IEEE DOI 1309
emotion recognition BibRef

Cheng, J.K.[Jin-Kuang], Deng, Y.D.[Yang-Dong], Meng, H.Y.[Hong-Ying], Wang, Z.H.[Zhi-Hua],
A facial expression based continuous emotional state monitoring system with GPU acceleration,
FG13(1-6)
IEEE DOI 1309
emotion recognition BibRef

Levesque, J.C., Morency, L.P.[Louis-Philippe], Gagne, C.,
Sequential emotion recognition using Latent-Dynamic Conditional Neural Fields,
FG13(1-6)
IEEE DOI 1309
emotion recognition BibRef

Baltrusaitis, T., Banda, N., Robinson, P.,
Dimensional affect recognition using Continuous Conditional Random Fields,
FG13(1-8)
IEEE DOI 1309
emotion recognition BibRef

Agarwal, S., Mukherjee, D.P.,
Decoding mixed emotions from expression map of face images,
FG13(1-6)
IEEE DOI 1309
emotion recognition BibRef

Marco-Giménez, L.[Luis], Arevalillo-Herráez, M.[Miguel], Cuhna-Pérez, C.[Cristina],
Eigenexpressions: Emotion Recognition Using Multiple Eigenspaces,
IbPRIA13(758-765).
Springer DOI 1307
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Dhall, A.[Abhinav], Joshi, J.[Jyoti], Radwan, I.[Ibrahim], Goecke, R.[Roland],
Finding Happiest Moments in a Social Context,
ACCV12(II:613-626).
Springer DOI 1304
BibRef

Cruz, A.C.[Albert C.], Bhanu, B.[Bir], Thakoor, N.S.[Ninad S.],
One shot emotion scores for facial emotion recognition,
ICIP14(1376-1380)
IEEE DOI 1502
BibRef
And:
Facial emotion recognition with anisotropic inhibited Gabor energy histograms,
ICIP13(4215-4219)
IEEE DOI 1402
BibRef
And: ICIP13(4215-4219)
IEEE DOI 1402
BibRef
Earlier:
Facial emotion recognition in continuous video,
ICPR12(1880-1883).
WWW Link. 1302
Avatars. Feature extraction BibRef

Verma, G.K.[Gyanendra K.], Singh, B.K.[Bhupesh Kumar],
Emotion recognition based on texture analysis of facial expression,
ICIIP11(1-6).
IEEE DOI 1112
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Yen, N.Y.[Nguwi Yok], Toe, T.T.[Teoh Teik],
Two-tier Emergent Self-Organizing (TtEsom) approach of understanding emotions,
ICARCV10(654-658).
IEEE DOI 1109
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Meng, H.Y.[Hong-Ying], Romera-Paredes, B.[Bernardino], Bianchi-Berthouze, N.[Nadia],
Emotion recognition by two view SVM_2K classifier on dynamic facial expression features,
FG11(854-859).
IEEE DOI 1103
BibRef

Littlewort, G.C.[Gwen C.], Whitehill, J.[Jacob], Wu, T.F.[Ting-Fan], Butko, N.[Nicholas], Ruvolo, P.[Paul], Movellan, J.R.[Javier R.], Bartlett, M.S.[Marian S.],
The motion in emotion: A CERT based approach to the FERA emotion challenge,
FG11(897-902).
IEEE DOI 1103

See also computer expression recognition toolbox (CERT), The. BibRef

Soleymani, M.[Mohammad], Koelstra, S.[Sander], Patras, I.[Ioannis], Pun, T.[Thierry],
Continuous emotion detection in response to music videos,
FG11(803-808).
IEEE DOI 1103
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Chatterjee, S.[Suvam], Shi, H.[Hao],
A Novel Neuro Fuzzy Approach to Human Emotion Determination,
DICTA10(282-287).
IEEE DOI 1012
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Li, S.[Shuo], Zhang, Y.J.[Yu-Jin], Tan, H.C.[Hua-Chun],
Discovering latent semantic factors for emotional picture categorization,
ICIP10(1065-1068).
IEEE DOI 1009
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Paleari, M.[Marco], Huet, B.[Benoit], Chellali, R.[Ryad],
Towards multimodal emotion recognition: a new approach,
CIVR10(174-181).
DOI Link 1007
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Du, Y.Z.[Yang-Zhou], Bi, W.Y.[Wen-Yuan], Wang, T.[Tao], Zhang, Y.M.[Yi-Min], Ai, H.Z.[Hai-Zhou],
Distributing expressional faces in 2-D emotional space,
CIVR07(395-400).
DOI Link 0707
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Matsukawa, T.[Tetsu], Hidaka, A.[Akinori], Kurita, T.[Takio],
Classification of Spectators' State in Video Sequences by Voting of Facial Expressions and Face Directions,
MVA09(426-).
PDF File. 0905
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Kim, M.Y.[Min-Young], Pavlovic, V.[Vladimir],
Structured Output Ordinal Regression for Dynamic Facial Emotion Intensity Prediction,
ECCV10(III: 649-662).
Springer DOI 1009

See also Multi-Output Laplacian Dynamic Ordinal Regression for Facial Expression Recognition and Intensity Estimation.
See also Discriminative Learning for Dynamic State Prediction. BibRef

Zheng, W.M.[Wen-Ming], Tang, H.[Hao], Lin, Z.C.[Zhou-Chen], Huang, T.S.[Thomas S.],
Emotion Recognition from Arbitrary View Facial Images,
ECCV10(VI: 490-503).
Springer DOI 1009
BibRef

Bernhardt, D.[Daniel], Robinson, P.[Peter],
Detecting Emotions from Connected Action Sequences,
IVIC09(1-11).
Springer DOI 0911
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Fazli, S.[Saeid], Afrouzian, R.[Reza], Seyedarabi, H.[Hadi],
A Combined KPCA and SVM Method for Basic Emotional Expressions Recognition,
ICMV09(84-88).
IEEE DOI 0912
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Qi, L.[Lin], Chen, E.Q.[En-Qing], Mu, X.M.[Xiao-Min], Guan, L.[Ling], Zhang, S.S.[Si-Si], Gao, L.[Lei],
Recognizing Human Emotional State Based on the 2D-FrFT and FLDA,
CISP09(1-4).
IEEE DOI 0910
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Khan, M.M.[Masood Mehmood], Ward, R.D.[Robert D.], Ingleby, M.[Michael],
Capturing Physiology of Emotion along Facial Muscles: A Method of Distinguishing Feigned from Involuntary Expressions,
CAIP09(1196-1203).
Springer DOI 0909
BibRef

Rojas Quińones, M.[Mario], Masip, D.[David], Vitriŕ, J.[Jordi],
Predicting dominance judgements automatically: A machine learning approach,
FG11(939-944).
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Facial features for social dominance estimation. BibRef

Rodo, D.M.[David Masip], Todorov, A.[Alexander], Vitriŕ Marca, J.[Jordi],
The Role of Facial Regions in Evaluating Social Dimensions,
Face12(II: 210-219).
Springer DOI 1210
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Chang, K.Y.[Kai-Yueh], Liu, T.L.[Tyng-Luh], Lai, S.H.[Shang-Hong],
Learning partially-observed hidden conditional random fields for facial expression recognition,
CVPR09(533-540).
IEEE DOI 0906
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Shang, L.F.[Li-Feng], Chan, K.P.[Kwok-Ping],
Nonparametric discriminant HMM and application to facial expression recognition,
CVPR09(2090-2096).
IEEE DOI 0906
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Ishii, M.[Masaki], Sato, K.[Kazuhito], Madokoro, H.[Hirokazu], Nishida, M.[Makoto],
Generation of emotional feature space based on topological characteristics of facial expression images,
FG08(1-6).
IEEE DOI 0809
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Valstar, M.F.[Michel F.], Colton, S.[Simon], Pantic, M.[Maja],
Emotionally aware automated portrait painting demonstration,
FG08(1-2).
IEEE DOI 0809
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Tamietto, M.[Marco], de Gelder, B.[Beatrice],
Emotional contagion for unseen bodily expressions: Evidence from facial EMG,
FG08(1-5).
IEEE DOI 0809
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Brizzi, J.[Jesse], Goldgof, D.B.[Dmitry B.], Sarkar, S.[Sudeep], Shreve, M.[Matthew],
Optical Flow Based Expression Suppression in Video,
ICPR14(1817-1821)
IEEE DOI 1412
Pattern recognition BibRef

Manohar, V.[Vasant], Shreve, M.[Matthew], Goldgof, D.B.[Dmitry B.], Sarkar, S.[Sudeep],
Modeling Facial Skin Motion Properties in Video and Its Application to Matching Faces across Expressions,
ICPR10(2122-2125).
IEEE DOI 1008
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Shreve, M.[Matthew], Godavarthy, S.[Sridhar], Goldgof, D.[Dmitry], Sarkar, S.[Sudeep],
Macro- and micro-expression spotting in long videos using spatio-temporal strain,
FG11(51-56).
IEEE DOI 1103
BibRef

Shreve, M.[Matthew], Godavarthy, S.[Sridhar], Manohar, V.[Vasant], Goldgof, D.[Dmitry], Sarkar, S.[Sudeep],
Towards macro- and micro-expression spotting in video using strain patterns,
WACV09(1-6).
IEEE DOI 0912
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Manohar, V.[Vasant], Shreve, M.[Matthew], Goldgof, D.B.[Dmitry B.], Sarkar, S.[Sudeep],
Finite element modeling of facial deformation in videos for computing strain pattern,
ICPR08(1-4).
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Yanulevskaya, V., van Gemert, J.C., Roth, K., Herbold, A.K., Sebe, N., Geusebroek, J.M.,
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ICIP08(101-104).
IEEE DOI 0810
BibRef

Hupont, I.[Isabelle], Baldassarri, S.[Sandra], del Hoyo, R.[Rafael], Cerezo, E.[Eva],
Effective Emotional Classification Combining Facial Classifiers and User Assessment,
AMDO08(xx-yy).
Springer DOI 0807
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Beszedes, M., Culverhouse, P.F.,
Facial Emotions and Emotion Intensity Levels Classification and Classification Evaluation,
BMVC07(xx-yy).
PDF File. 0709
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Arifin, S., Cheung, P.Y.K.,
User Attention Based Arousal Content Modeling,
ICIP06(433-436).
IEEE DOI 0610
Evaluate the emotion in the video. BibRef

Wong, J.J.[Jia-Jun], Cho, S.Y.[Siu-Yeung],
Adaptive Processing of Face Emotion Tree Structures,
ICPR06(I: 1184-1187).
IEEE DOI 0609
BibRef

Kobayashi, Y.[Yuichi], Ohya, J.[Jun],
EM-in-M: Analyze and Synthesize Emotion in Motion,
IWICPAS06(135-143).
Springer DOI 0608
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Li, H.B.[Hui-Bin], Huang, D.[Di], Lemaire, P.[Pierre], Morvan, J.M.[Jean-Marie], Chen, L.M.[Li-Ming],
Expression Robust 3D Face Recognition via Mesh-Based Histograms of Multiple Order Surface Differential Quantities,
ICIP11(3053-3056).
IEEE DOI 1201
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Li, H.B.[Hui-Bin], Morvan, J.M.[Jean-Marie], Chen, L.M.[Li-Ming],
3D Facial Expression Recognition Based on Histograms of Surface Differential Quantities,
ACIVS11(483-494).
Springer DOI 1108
BibRef

Livingston, A.R.[Adam R.], Seow, M.J.[Ming-Jung], Asari, V.K.[Vijayan K.],
A Binary Decision Tree Based Real-Time Emotion Detection System,
ISVC07(I: 432-441).
Springer DOI 0711
BibRef

Altun, H.[Halis], Polat, G.[Gökhan],
New Frameworks to Boost Feature Selection Algorithms in Emotion Detection for Improved Human-Computer Interaction,
BVAI07(533-541).
Springer DOI 0710
BibRef

Shin, Y.S.[Young-Suk],
Recognizing Facial Expressions with PCA and ICA onto Dimension of the Emotion,
SSPR06(916-922).
Springer DOI 0608
BibRef
And:
Facial Expression Recognition in Various Internal States Using Independent Component Analysis,
AMDO06(291-299).
Springer DOI 0607
BibRef
Earlier:
The Effect of Facial Expression Recognition Based on the Dimensions of Emotion Using PCA Representation and Neural Networks,
ICIAR05(1133-1140).
Springer DOI 0509
BibRef
Earlier:
Facial Expression Recognition Based on Dimension Model of Emotion with Autonomously Extracted Sparse Representations,
ICBA04(81-87).
Springer DOI 0505
BibRef

Kang, H.B.[Hang-Bong],
Emotional event detection using relevance feedback,
ICIP03(I: 721-724).
IEEE DOI 0312
BibRef

Raouzaiou, A., Karpouzis, K., Kollias, S.,
Online Gaming and Emotion Representation,
VLBV03(298-305).
Springer DOI 0310
BibRef

Reynolds, C.[Carson],
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Vismod559, May 2001.
HTML Version. 0306
BibRef

Du, Y.Z.[Yang-Zhou], Lin, X.[Xucyin],
Mapping emotional status to facial expressions,
ICPR02(II: 524-527).
IEEE DOI 0211
BibRef

Sebe, N., Lew, M.S., Cohen, I.[Ira], Garg, A., Huang, T.S.,
Emotion recognition using a cauchy naive bayes classifier,
ICPR02(I: 17-20).
IEEE DOI 0211

See also Facial Expression Recognition from Video Sequences: Temporal and Static Modeling. BibRef

Chapter on Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics continues in
Emotion Recognition, Deep Learning .


Last update:Jul 13, 2024 at 15:27:21