More Web Proxy on the site http://driver.im/

research-article

Automatic Analysis of Facial Expressions: The State of the Art

Authors:

Leon J. M. RothkrantzAuthors Info & Claims

IEEE Transactions on Pattern Analysis and Machine Intelligence, Volume 22, Issue 12

Pages 1424 - 1445

https://doi.org/10.1109/34.895976

Published: 01 December 2000 Publication History

Abstract

Humans detect and interpret faces and facial expressions in a scene with little or no effort. Still, development of an automated system that accomplishes this task is rather difficult. There are several related problems: detection of an image segment as a face, extraction of the facial expression information, and classification of the expression (e.g., in emotion categories). A system that performs these operations accurately and in real time would form a big step in achieving a human-like interaction between man and machine. This paper surveys the past work in solving these problems. The capability of the human visual system with respect to these problems is discussed, too. It is meant to serve as an ultimate goal and a guide for determining recommendations for development of an automatic facial expression analyzer.

References

[1]

J.N. Bassili, “Facial Motion in the Perception of Faces and of Emotional Expression,” J. Experimental Psychology 4, pp. 373-379, 1978.

[2]

M.J. Black and Y. Yacoob, “Recognizing Facial Expressions in Image Sequences Using Local Parameterized Models of Image Motion,” lnt'l J. Computer Vision, vol. 25, no. 1, pp. 23-48, 1997.

Digital Library

[3]

M.J. Black and Y. Yacoob, “Tracking and Recognizing Rigid and Non-Rigid Facial Motions Using Local Parametric Models of Image Motions,” Proc. Int'l Conf. Computer Vision, pp. 374-381, 1995.

Digital Library

[4]

E. Boyle A.H. Anderson and A. Newlands, “The Effects of Visibility on Dialogue in a Cooperative Problem Solving Task,” Language and Speech, vol. 37, no. 1, pp. 1-20, 1994.

[5]

V. Bruce, Recognizing Faces. Hove, East Sussex: Lawrence Erlbaum Assoc., 1986.

[6]

V. Bruce, “What the Human Face Tells the Human Mind: Some Challenges for the Robot-Human Interface,” Proc. Int'l Workshop Robot and Human Comm., pp. 44-51, 1992.

[7]

J. Buhmann J. Lange and C. von der Malsburg, “Distortion Invariant Object Recognition—Matching Hierarchically Labelled Graphs,” Proc. Int'l Joint Conf. Neural Networks, pp. 155-159, 1989.

[8]

F.W. Campbell, “How Much of the Information Falling on the Retina Reaches the Visual Cortex and How Much is Stored in the Memory?” Seminar at the Pontificae Academiae Scientiarium Scripta Varia, 1983.

[9]

L.S. Chen T.S. Huang T. Miyasato and R. Nakatsu, “Multimodal Human Emotion/Expression Recognition,” Proc. Int'l Conf. Automatic Face and Gesture Recognition, pp. 366-371, 1998.

Digital Library

[10]

J.F. Cohn A.J. Zlochower J.J. Lien and T. Kanade, “Feature-Point Tracking by Optical Flow Discriminates Subtle Differences in Facial Expression,” Proc. Int'l Conf. Automatic Face and Gesture Recognition, pp. 396-401, 1998.

Digital Library

[11]

T.F. Cootes C.J. Taylor D.H. Cooper and J. Graham, “Active Shape Models—Training and Application,” Computer Vision Image Understanding, vol. 61, no. 1, pp. 38-59, 1995.

Digital Library

[12]

T.F. Cootes G.J. Edwards and C.J. Taylor, “Active Appearance Models,” Proc. European Conf. Computer Vision, vol. 2, pp. 484-498, 1998.

Digital Library

[13]

G.W. Cottrell and J. Metcalfe, “EMPATH: Fface, Emotion, Gender Recognition Using Holons,” Advances in Neural Information Processing Systems 3, R.P. Lippman, ed., pp. 564-571, 1991.

Digital Library

[14]

D. DeCarlo D. Metaxas and M. Stone, “An Anthropometric Face Model Using Variational Techniques,” Proc. SIGGRAPH, pp. 67-74, 1998.

Digital Library

[15]

L.C. De Silva T. Miyasato and R. Nakatsu, “Facial Emotion Recognition Using Multimodal Information,” Proc. Information, Comm., and Signal Processing Conf., pp. 397-401, 1997.

[16]

G. Donato M.S. Bartlett J.C. Hager P. Ekman and T.J. Sejnowski, “Classifying Facial Actions,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 21, no. 10, pp. 974-989, Oct. 1999.

Digital Library

[17]

M.S. Bartlett J.C. Hager P. Ekman and T.J. Sejnowski, “Measuring Facial Expressions by Computer Image Analysis,” Psychophysiology, vol. 36, pp. 253-263, 1999.

[18]

G.J. Edwards T.F. Cootes and C.J. Taylor, “Face Recognition Using Active Appearance Models,” Proc. European Conf. Computer Vision, vol. 2, pp. 581-695, 1998.

Digital Library

[19]

P. Eisert and B. Girod, “Analysing Facial Expressions for Virtual Conferencing,” IEEE Trans Computer Graphics and Applications, vol. 18, no. 5, pp. 70-78, 1998.

Digital Library

[20]

P. Ekman and W.V. Friesen, Unmasking the Face. New Jersey: Prentice Hall, 1975.

[21]

P. Ekman and W.V. Friesen, Facial Action Coding System (FACS): Manual. Palo Alto: Consulting Psychologists Press, 1978.

[22]

P. Ekman, Emotion in the Human Face. Cambridge Univ. Press, 1982.

[23]

H.D. Ellis, “Process Underlying Face Recognition,” The Neuropsychology of Face Perception and Facial Expression, R. Bruyer, ed. pp. 1-27, New Jersey: Lawrence Erlbaum Assoc., 1986.

[24]

I. Essa and A. Pentland, “Coding, Analysis Interpretation, Recognition of Facial Expressions,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 19, no. 7, pp. 757-763, July 1997.

Digital Library

[25]

A.J. Fridlund P. Ekman and H. Oster, “Facial Expressions of Emotion: Review Literature 1970-1983,” Nonverbal Behavior and Communication, A.W. Siegman and S. Feldstein, eds., pp. 143-224. Hillsdale NJ: Lawrence Erlbaum Assoc., 1987.

[26]

A.J. Fridlund, “Evolution and Facial Action in Reflex, Social Motive, and Paralanguage,” Biological Psychology, vol. 32, pp. 3-100, 1991.

[27]

D.J. Hand, Discrimination and Classification. John Wiley and Sons, 1981.

[28]

F. Hara and H. Kobayashi, “State of the Art in Component Development for Interactive Communication with Humans,” Advanced Robotics, vol. 11, no. 6, pp. 585-604, 1997.

[29]

R.J. Holt T.S. Huang A.N. Netravali and R.J. Qian, “Determining Articulated Motion from Perspective Views,” Pattern Recognition, vol. 30, no. 9, pp. 1435-1,449, 1997.

[30]

H. Hong H. Neven and C. von der Malsburg, “Online Facial Expression Recognition Based on Personalized Galleries,” Proc. Int'l Conf. Automatic Face and Gesture Recognition, pp. 354-359, 1998.

Digital Library

[31]

B. Horn and B. Schunck, “Determining Optical Flow,” Artificial Intelligence, vol. 17, pp. 185-203, 1981.

Digital Library

[32]

C.L. Huang and Y.M. Huang, “Facial Expression Recognition Using Model-Based Feature Extraction and Action Parameters Classification,” J. Visual Comm. and Image Representation, vol. 8, no. 3, pp. 278-290, 1997.

Digital Library

[33]

C.E. Izard, The Face of Emotion. New York: Appleton-Century-Crofts, 1971.

[34]

C.E. Izard, “Facial Expressions and the Regulation of Emotions,” J. Personality and Social Psychology, vol. 58, no. 3, pp. 487-498, 1990.

[35]

T. Johanstone R. Banse and K.S. Scherer, “Acoustic Profiles in Prototypical Vocal Expressions of Emotions,” Proc. Int'l Conf. Phonetic Science, vol. 4, pp. 2-5, 1995.

[36]

I. Kanter and H. Sompolinsky, “Associative Recall of Memory without Errors” Physical Review, vol. 35, no. 1, pp. 380-392, 1987.

[37]

M. Kass A. Witkin and D. Terzopoulos, “Snake: Active Contour Model,” Proc. Int'l Conf. Computer Vision, pp. 259-269, 1987.

[38]

M. Kato I. So Y. Hishinuma O. Nakamura and T. Minami, “Description and Synthesis of Facial Expressions Based on Isodensity Maps,” Visual Computing, T. Kunii, ed., pp. 39-56. Tokyo: Springer-Verlag, 1991.

Digital Library

[39]

F. Kawakami M. Okura H. Yamada H. Harashima and S. Morishima, “3D Emotion Space for Interactive Communication,” Proc. Computer Science Conf., pp. 471-478, 1995.

Digital Library

[40]

G.D. Kearney and S. McKenzie, “Machine Interpretation of Emotion: Design of Memory-Based Expert System for Interpreting Facial Expressions in Terms of Signaled Emotions (JANUS),” Cognitive Science, vol. 17, no. 4, pp. 589-622, 1993.

[41]

S. Kimura and M. Yachida, “Facial Expression Recognition and Its Degree Estimation,” Proc. Computer Vision and Pattern Recognition, pp. 295-300, 1997.

Digital Library

[42]

H. Kobayashi and F. Hara, “Facial Interaction between Animated 3D Face Robot and Human Beings,” Proc. Int'l Conf. Systems, Man, Cybernetics, pp. 3,732-3,737, 1997.

[43]

H. Kobayashi and F. Hara, “Recognition of Six Basic Facial Expressions and Their Strength by Neural Network,” Proc. Int'l Workshop Robot and Human Comm., pp. 381-386, 1992.

[44]

H. Kobayashi and F. Hara, “Recognition of Mixed Facial Expressions by Neural Network,” Proc. Int'l Workshop Robot and Human Comm., pp. 387-391, 1992.

[45]

K.M. Lam and H. Yan, “An Analytic-to-Holistic Approach for Face Recognition Based on a Single Frontal View,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 20, no. 7, pp. 673-686, July 1998.

Digital Library

[46]

H.K. Lee and J.H. Kim, “An HMM-Based Threshold Model Approach for Gesture Recognition,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 21, no. 10, pp. 961-973, Oct. 1999.

Digital Library

[47]

H. Li and P. Roivainen, “3D Motion Estimation in Model-Based Facial Image Coding,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 15, no. 6, pp. 545-555, 1993.

Digital Library

[48]

J.J. Lien T. Kanade J.F. Cohn and C.C. Li, “Automated Facial Expression Recognition Based on FACS Action Units,” Proc. Int'l Conf. Automatic Face and Gesture Recognition, pp. 390-395, 1998.

Digital Library

[49]

B. Lucas and T. Kanade, “An Iterative Image Registration Technique with an Application to Stereo Vision,” Proc. Joint Conf. Artificial Intelligence, pp. 674-680, 1981.

[50]

M.J. Lyons S. Akamatsu M. Kamachi and J. Gyoba, “Coding Facial Expressions with Gabor Wavelets,” Proc. Int'l Conf. Automatic Face and Gesture Recognition, pp. 200-205, 1998.

Digital Library

[51]

M.J. Lyons J. Budynek and S. Akamatsu, “Automatic Classification of Single Facial Images,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 21, no. 12, pp. 1,357-1,362, 1999.

Digital Library

[52]

K. Mase, “Recognition of Facial Expression from Optical Flow,” IEICE Trans., vol. E74, no. 10, pp. 3,474-3,483, 1991.

[53]

K. Matsumura Y. Nakamura and K. Matsui, ”Mathematical Representation and Image Generation of Human Faces by Metamorphosis,” Electronics and Comm. in Japan—3, vol. 80, no. 1, pp. 36-46, 1997.

[54]

K. Matsuno C.W. Lee and S. Tsuji, “Recognition of Facial Expression with Potential Net,” Proc. Asian Conf. Computer Vision, pp. 504-507, 1993.

[55]

A. Mehrabian, “Communication without Words,” Psychology Today, vol. 2, no. 4, pp. 53-56, 1968.

[56]

S. Morishima F. Kawakami H. Yamada and H. Harashima, “A Modelling of Facial Expression and Emotion for Recognition and Synthesis,” Symbiosis of Human and Artifact, Y. Anzai, K. Ogawa and H. Mori, eds., pp. 251-256, Amsterdam: Elsevier Science BV, 1995.

[57]

Y. Moses D. Reynard and A. Blake, “Determining Facial Expressions in Real Time,” Proc. Int'l Conf. Automatic Face and GestureRecognition, pp. 332-337, 1995.

[58]

R. Nakatsu, “Toward the Creation of a New Medium for the Multimedia Era,” Proc. IEEE, vol. 86, no. 5, pp. 825-836, 1998.

[59]

T. Otsuka and J. Ohya, “Recognition of Facial Expressions Using HMM with Continuous Output Probabilities,” Proc. Int'l Workshop Robot and Human Comm., pp. 323-328, 1996.

[60]

T. Otsuka and J. Ohya, “Spotting Segments Displaying Facial Expression from Image Sequences Using HMM,” Proc. Int'l Conf. Automatic Face and Gesture Recognition, pp. 442-447, 1998.

Digital Library

[61]

C. Padgett and G.W. Cottrell, “Representing Face Images for Emotion Classification,” Proc. Conf. Advances in Neural Information Processing Systems, pp. 894-900, 1996.

[62]

M. Pantic and L.J.M. Rothkrantz, “Expert System for Automatic Analysis of Facial Expression,” Image and Vision Computing J., vol. 18, no. 11, pp. 881-905, 2000.

[63]

M. Pantic and L.J.M. Rothkrantz, “An Expert System for Multiple Emotional Classification of Facial Expressions” Proc. Int'l Conf. Tools with Artificial Intelligence, pp. 113-120, 1999.

Digital Library

[64]

V.I. Pavlovic R. Sharma and T.S. Huang, “Visual Interpretation of Hand Gestures for Human-Computer Interaction: Review,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 19, no. 7, pp. 677-695, 1997.

Digital Library

[65]

A. Pentland B. Moghaddam and T. Starner, “View-Based and Modular Eigenspaces for Face Recognition,” Proc. Computer Vision and Pattern Recognition, pp. 84-91, 1994.

[66]

V.A. Petrushin, “Emotion in Speech: Recognition and Application to Call Centers,” Proc. Conf. Artificial Neural Networks in Eng., 1999.

[67]

R.W. Picard and E. Vyzas, “Offline and Online Recognition of Emotion Expression from Physiological Data,” Emotion-Based Agent Architectures Workshop Notes, Int'l Conf. Autonomous Agents, pp. 135-142, 1999.

[68]

T.S. Polzin and A.H. Waibel, “Detecting Emotions in Speech,” Proc. Conf. Cooperative Multimedia Comm., 1998.

[69]

W.H. Press S.A. Teukolsky W.T. Vetterling and B.P. Flannery, Numerical Recipes in C, Cambridge Univ. Press, 1992.

Digital Library

[70]

A. Rahardja A. Sowmya and W.H. Wilson, “A Neural Network Approach to Component versus Holistic Recognition of Facial Expressions in Images,” SPIE, Intelligent Robots and Computer Vision X: Algorithms and Techniques, vol. 1, 607, pp. 62-70, 1991.

[71]

A. Ralescu and R. Hartani, “Some Issues in Fuzzy and Linguistic Modeling” Proc. Conf. Fuzzy Systems, pp. 1,903-1,910, 1995.

[72]

M. Riedmiller and H. Braun, “A Direct Adaptive Method for Faster Backpropagation Learning: The RPROP Algorithm,” Proc. Int'l Conf. Neural Networks, pp. 586-591, 1993.

[73]

M. Rosenblum Y. Yacoob and L. Davis, “Human Emotion Recognition from Motion Using a Radial Basis Function Network Architecture,” Proc. IEEE Workshop on Motion of Non-Rigid and Articulated Objects, pp. 43-49, 1994.

[74]

H.A. Rowley S. Baluja and T. Kanade, “Neural Network-Based Face Detection,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 20, no. 1, pp. 23-38, Jan. 1998.

Digital Library

[75]

The Psychology of Facial Expression, J.A. Russell and J.M. Fernandez-Dols, eds. Cambridge: Cambridge Univ. Press, 1997.

[76]

J.A. Russell, “Is There Universal Recognition of Emotion from Facial Expression?” Psychological Bulletin, vol. 115, no. 1, pp. 102-141, 1994.

[77]

P. Ekman, “Strong Evidence for Universals in Facial Expressions: A Reply to Russell's Mistaken Critique,” Psychological Bulletin, vol. 115, no. 2, pp. 268-287, 1994.

[78]

A. Samal, “Minimum Resolution for Human Face Detection and Identification,” SPIE Human Vision, Visual Processing, and Digital Display II, vol. 1, 453, pp. 81-89, 1991.

[79]

A. Samal and P.A. Iyengar, “Automatic Recognition and Analysis of Human Faces and Facial Expressions: A Survey,” Pattern Recognition, vol. 25, no. 1, pp. 65-77, 1992.

Digital Library

[80]

E. Simoncelli, “Distributed Representation and Analysis of Visual Motion,” PhD thesis, Massachusetts Inst. of Technology, 1993.

Digital Library

[81]

J. Steffens E. Elagin and H. Neven, “PersonSpotter—Fast and Robust System for Human Detection, Tracking, and Recognition,” Proc. Int'l Conf. Automatic Face and Gesture Recognition, pp. 516-521, 1998.

Digital Library

[82]

G.M. Stephenson K. Ayling D.R. Rutter, “The Role of Visual Communication in Social Exchange,” Britain J. Social Clinical Psychology, vol. 15, pp. 113-120, 1976.

[83]

K.K. Sung and T. Poggio, “Example-Based Learning for View-Based Human Face Detection” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 20, no. 1, pp. 39-51, Jan. 1998.

Digital Library

[84]

A. Takeuchi and K. Nagao, “Communicative Facial Displays as a New Conversational Modality,” Proc. ACM INTERCHI, pp. 187-193, 1993.

Digital Library

[85]

J.C. Terrillon M. David and S. Akamatsu, “Automatic Detection of Human Faces in Natural Scene Images by Use of a Skin Color Model of Invariant Moments” Proc. Int'l Conf. Automatic Face and Gesture Recognition, pp. 112-117, 1998.

Digital Library

[86]

D. Terzopoulos and K. Waters, “Analysis and Synthesis of Facial Image Sequences Using Physical and Anatomical Models,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 15, no. 6, pp. 569-579, June 1993.

Digital Library

[87]

N.M. Thalmann and D. Thalmann, “600 Indexed References on Computer Animation,” J. Visualisation and Computer Animation, vol. 3, pp. 147-174, 1992.

[88]

N.M. Thalmann P. Kalra and M. Escher, “Face to Virtual Face,” Proc. IEEE, vol. 86, no. 5, pp. 870-883, 1998.

[89]

N.M. Thalmann P. Kalra and I.S. Pandzic, “Direct Face-to-Face Communication between Real and Virtual Humans” Int'l J. Information Technology, vol. 1, no. 2, pp. 145-157, 1995.

[90]

N. Tosa and R. Nakatsu, “Life-Like Communication Agent—Emotion Sensing Character MIC and Feeling Session Character MUSE,” Proc. Conf. Multimedia Computing and Systems, pp. 12-19, 1996.

Digital Library

[91]

M. Turk and A. Pentland, “Eigenfaces for Recognition,” J. Cognitive Neuroscience, vol. 3, no. 1, pp. 71-86, 1991.

Digital Library

[92]

H. Ushida T. Takagi and T. Yamaguchi, “Recognition of Facial Expressions Using Conceptual Fuzzy Sets” Proc. Conf. Fuzzy Systems, vol. 1, pp. 594-599, 1993.

[93]

P. Vanger R. Honlinger and H. Haken, “Applications of Synergetics in Decoding Facial Expression of Eemotion,” Proc. Int'l Conf. Automatic Face and Gesture Recognition, pp. 24-29, 1995.

[94]

J.M. Vincent D.J. Myers and R.A. Hutchinson, “Image Feature Location in Multi-Resolution Images Using a Hierarchy of Multi-Layer Preceptors,” Neural Networks for Speech, Vision, and Natural Language, pp. 13-29, Chapman & Hall, 1992.

[95]

M. Wang Y. Iwai and M. Yachida, “Expression Recognition from Time-Sequential Facial Images by Use of Expression Change Model,” Proc. Int'l Conf. Automatic Face and Gesture Recognition, pp. 324-329, 1998.

Digital Library

[96]

D.J. Williams and M. Shah, “A Fast Algorithm for Active Contours and Curvature Estimation,” Computer Vision and Image Processing: Image Understanding, vol. 55, no. 1, pp. 14-26, 1992.

Digital Library

[97]

A.D. Wilson and A.F. Bobick, “Parametric Hidden Markov Models for Gesture Recognition” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 21, no. 9, pp. 884-900, Sept. 1999.

Digital Library

[98]

L. Wiskott, “Labelled Graphs and Dynamic Link Matching for Face Recognition and Scene Analysis,” Reihe Physik, vol. 53, Frankfurt a.m. Main: Verlag Harri Deutsch, 1995.

[99]

H. Wu T. Yokoyama D. Pramadihanto and M. Yachida, “Face and Facial Feature Extraction from Color Image,” Proc. Int'l Conf. Automatic Face and Gesture Recognition, pp. 345-350, 1996.

Digital Library

[100]

Y. Yacoob and L. Davis, “Recognizing Facial Expressions by Spatio-Temporal Analysis,” Proc. Int'l Conf. Pattern Recognition, vol. 1, pp. 747-749, 1994.

[101]

Y. Yacoob and L. Davis, “Computing Spatio-Temporal Representations of Human Faces,” Proc. Computer Vision and Pattern Recognition, pp. 70-75, 1994.

[102]

H. Yamada, “Visual Information for Categorizing Facial Expressions of Emotions,” Applied Cognitive Psychology, vol. 7, pp. 257-270, 1993.

[103]

J. Yang and A. Waibel, “A Real-Time Face Tracker,” Workshop Applications of Computer Vision, pp. pp. 142-147, 1996.

Digital Library

[104]

M. Yoneyama Y. Iwano A. Ohtake and K. Shirai, “Facial Expressions Recognition Using Discrete Hopfield Neural Networks,” Proc. Int'l Conf. Information Processing, vol. 3, pp. 117-120, 1997.

Digital Library

[105]

A.L. Yuille D.S. Cohen and P.W. Hallinan, “Feature Extraction from Faces Using Deformable Templates,” Proc. Computer Vision and Pattern Recognition, pp. 104-109, 1989.

[106]

Z. Zhang M. Lyons M. Schuster and S. Akamatsu, “Comparison between Geometry-Based and Gabor Wavelets-Based Facial Expression Recognition Using Multi-Layer Perceptron,” Proc. Int'l Conf. Automatic Face and Gesture Recognition, pp. 454-459, 1998.

Digital Library

[107]

J. Zhao and G. Kearney, “Classifying Facial Emotions by Backpropagation Neural Networks with Fuzzy Inputs,” Proc. Conf. Neural Information Processing, vol. 1, pp. 454-457, 1996.

Cited By

Xu YJiang XWu D(2024)Cross-Task Inconsistency Based Active Learning (CTIAL) for Emotion RecognitionIEEE Transactions on Affective Computing10.1109/TAFFC.2024.336676715:3(1659-1668)Online publication date: 1-Jul-2024
https://dl.acm.org/doi/10.1109/TAFFC.2024.3366767
Talaat FAli ZMostafa REl-Rashidy N(2024)Real-time facial emotion recognition model based on kernel autoencoder and convolutional neural network for autism childrenSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-023-09477-y28:9-10(6695-6708)Online publication date: 1-May-2024
https://dl.acm.org/doi/10.1007/s00500-023-09477-y
Freitas RAires Kde Paiva AVeras RSoares P(2024)A CNN-based multi-level face alignment approach for mitigating demographic bias in clinical populationsComputational Statistics10.1007/s00180-023-01395-939:5(2557-2579)Online publication date: 1-Jul-2024
https://dl.acm.org/doi/10.1007/s00180-023-01395-9
Show More Cited By

Index Terms

Automatic Analysis of Facial Expressions: The State of the Art
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision problems
        Image segmentation
        Object recognition
        Video segmentation
2. Human-centered computing
  1. Human computer interaction (HCI)

Recommendations

Overview of automatic facial expressions analysis
VIIP '07: The Seventh IASTED International Conference on Visualization, Imaging and Image Processing

The development of an automated system for facial expression analysis or interpret is rather difficult. There are several related problems: detection of an image segment as a face, extraction of the facial expression information, and classification of ...
Effective semantic features for facial expressions recognition using SVM

Most traditional facial expression-recognition systems track facial components such as eyes, eyebrows, and mouth for feature extraction. Though some of these features can provide clues for expression recognition, other finer changes of the facial ...
Automatic recognition and analysis of human faces and facial expressions: a survey

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image IEEE Transactions on Pattern Analysis and Machine Intelligence

IEEE Transactions on Pattern Analysis and Machine Intelligence Volume 22, Issue 12

December 2000

154 pages

ISSN:0162-8828

Editor:
Kevin Bowler
Univ. of Florida State, Tampa, Fl

Issue’s Table of Contents

Copyright © Copyright © 2000 IEEE. All Rights Reserved.

Publisher

IEEE Computer Society

United States

Publication History

Published: 01 December 2000

Author Tags

Qualifiers

Research-article

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

321
Total Citations
View Citations
0
Total Downloads

Downloads (Last 12 months)0
Downloads (Last 6 weeks)0

Reflects downloads up to 11 Dec 2024

Other Metrics

View Author Metrics

Citations

Cited By

Xu YJiang XWu D(2024)Cross-Task Inconsistency Based Active Learning (CTIAL) for Emotion RecognitionIEEE Transactions on Affective Computing10.1109/TAFFC.2024.336676715:3(1659-1668)Online publication date: 1-Jul-2024
https://dl.acm.org/doi/10.1109/TAFFC.2024.3366767
Talaat FAli ZMostafa REl-Rashidy N(2024)Real-time facial emotion recognition model based on kernel autoencoder and convolutional neural network for autism childrenSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-023-09477-y28:9-10(6695-6708)Online publication date: 1-May-2024
https://dl.acm.org/doi/10.1007/s00500-023-09477-y
Freitas RAires Kde Paiva AVeras RSoares P(2024)A CNN-based multi-level face alignment approach for mitigating demographic bias in clinical populationsComputational Statistics10.1007/s00180-023-01395-939:5(2557-2579)Online publication date: 1-Jul-2024
https://dl.acm.org/doi/10.1007/s00180-023-01395-9
Nasihati Gilani SPollard KTraum D(2023)Multimodal Prediction of User's Performance in High-Stress Dialogue InteractionsCompanion Publication of the 25th International Conference on Multimodal Interaction10.1145/3610661.3617166(71-75)Online publication date: 9-Oct-2023
https://dl.acm.org/doi/10.1145/3610661.3617166
Oralbayeva NAly ASandygulova ABelpaeme T(2023)Data-driven Communicative Behaviour Generation: A SurveyACM Transactions on Human-Robot Interaction10.1145/360923513:1(1-39)Online publication date: 16-Aug-2023
https://dl.acm.org/doi/10.1145/3609235
Sun LLian ZLiu BTao JEl Saddik AMei TCucchiara RBertini MTobon Vallejo DAtrey PHossain M(2023)MAE-DFER: Efficient Masked Autoencoder for Self-supervised Dynamic Facial Expression RecognitionProceedings of the 31st ACM International Conference on Multimedia10.1145/3581783.3612365(6110-6121)Online publication date: 26-Oct-2023
https://dl.acm.org/doi/10.1145/3581783.3612365
Shi JYang HCarlone L(2023)Optimal and Robust Category-Level Perception: Object Pose and Shape Estimation From 2-D and 3-D Semantic KeypointsIEEE Transactions on Robotics10.1109/TRO.2023.327727339:5(4131-4151)Online publication date: 1-Oct-2023
https://dl.acm.org/doi/10.1109/TRO.2023.3277273
Zhu JLuo BYang TWang ZZhao XGao Y(2023)Knowledge Conditioned Variational Learning for One-Class Facial Expression RecognitionIEEE Transactions on Image Processing10.1109/TIP.2023.329377532(4010-4023)Online publication date: 1-Jan-2023
https://dl.acm.org/doi/10.1109/TIP.2023.3293775
Hsu JWu C(2023)Applying Segment-Level Attention on Bi-Modal Transformer Encoder for Audio-Visual Emotion RecognitionIEEE Transactions on Affective Computing10.1109/TAFFC.2023.325890014:4(3231-3243)Online publication date: 1-Oct-2023
https://dl.acm.org/doi/10.1109/TAFFC.2023.3258900
Ezzameli KMahersia H(2023)Emotion recognition from unimodal to multimodal analysisInformation Fusion10.1016/j.inffus.2023.10184799:COnline publication date: 1-Nov-2023
https://dl.acm.org/doi/10.1016/j.inffus.2023.101847
Show More Cited By

View Options

View options

Media

Figures

Other

Tables

View Issue’s Table of Contents