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A Comprehensive Survey on Human Facial Expression Detection
Archana Verma, Lokesh Kumar Sharma
Pages - 171 - 182 | Revised - 05-04-2013 | Published - 30-04-2013
Published in International Journal of Image Processing (IJIP)
MORE INFORMATION
KEYWORDS
Facial Expression, FACS, Fuzzy Inference System, Feature Extraction, HCI.
ABSTRACT
In the recent years recognition of Human's Facial Expression has been very active research area
in computer vision. There have been several advances in the past few years in terms of face
detection and tracking, feature extraction mechanisms and the techniques used for expression
classification. This paper surveys some of the published work since 2001. The paper gives a
time-line view of the advances made in this field, the applications of automatic face expression
recognizers, the characteristics of an ideal system, the databases that have been used and the
advances made in terms of their standardization and a detailed summary of the state of the art.
The paper also discusses facial parameterization using FACS Action Units (AUs) and advances
in face detection, tracking and feature extraction methods. It has the important role in the humancomputer
interaction (HCI) systems. There are multiple methods devised for facial feature
extraction which helps in identifying face and facial expressions.
1 | Mohammed, S. N., George, L. E., & Dawood, H. A. The Effect of Classification Methods on Facial Emotion Recognition Accuracy. |
2 | Perikos, I., Ziakopoulos, E., & Hatzilygeroudis, I. (2015). Recognize Emotions from Facial Expressions Using a SVM and Neural Network Schema. In Engineering Applications of Neural Networks (pp. 265-274). Springer International Publishing. |
3 | Casaburi, L., Colace, F., De Santo, M., & Greco, L. (2015). “Magic mirror in my hand, what is the sentiment in the lens?”: An action unit based approach for mining sentiments from multimedia contents. Journal of Visual Languages & Computing, 27, 19-28. |
4 | Erna, A., Yu, L., Zhao, K., Chen, W., & Suzuki, E. (2014). Facial Expression Data Constructed with Kinect and Their Clustering Stability. In Active Media Technology (pp. 421-431). Springer International Publishing. |
5 | Kondo, R., Deguchi, Y., & Suzuki, E. (2014). Developing a Face Monitoring Robot for a Desk Worker. In Ambient Intelligence (pp. 226-241). Springer International Publishing. |
6 | Perikos, I., Ziakopoulos, E., & Hatzilygeroudis, I. (2014). Recognizing Emotions from Facial Expressions Using Neural Network. In Artificial Intelligence Applications and Innovations (pp. 236-245). Springer Berlin Heidelberg. |
7 | Barbas, H. (2013). Avatars and the «Imitation Game»–can machines smile. |
A. C. Koutlas and D. I. Fotiadis. “A Region Based Methodology for facial expression recognition”, IEEE Int. Conf. on Systems, Man and Cybernetics, 2008, pp. 662 - 666. | |
A. Jamshidnezhad, J. Nordin. “A Classifier Model based on the Features Quantitative Analysis for Facial Expression Recognition”, Proceeding of the International Conference on Advanced Science, Engineering and Information Technology, 2011. | |
C. Shan, S. Gong and P. W. McOwan. “Facial expression recognition based on Local Binary Patterns: A comprehensive study” Image and Vision Computing, Vol. 27, pp. 803-816. May 2009. | |
D. Arumugam and S. Purushothaman. “Emotion Classification using Facial Expression”International Journal of Advanced Computer Science and Applications, Vol. 2, No.7, pp. 92-,98, 2011. | |
Derbaix, C. M. “The Impact of Affective Reactions on Attitudes toward the Advertisement and the Brand: A Step toward Ecological Validity”, Journal of Marketing Research, Vol. 32(November): 470-479, 1995. | |
G. Fanelli, A. Yao, P. Noel, J. Gall, and L. Gool. “Hough Forest-based Facial Expression Recognition from Video Sequences”, International Workshop on Sign, Gesture and Activity (SGA’10), Springer LNCS 6553, 2012, pp. 195-206. | |
G. Littlewort et al. "Dynamics of facial expression extracted automatically from video", Image and Vision Computing Vol. 24, pp. 615-625, 2006. | |
H. Deng, L. Jin, L. Zhen, and J. Huang. “A New Facial Expression Recognition Method based on Local Gabor Filter Bank and PCA plus LDA”, International Journal of Information Technology, Vol. 11, No. 11, pp. 86-96, 2005. | |
I. Kotsia and I. Patras. “Facial Expression Recognition in Image Sequences using Geometric Deformation Features and SVM”, IEEE Transactions on Image Processing Vol. 16, No.1, pp.172-187, Jan 2007. | |
J. Xiao, S. Baker, I. Matthews, and T. Kanade. Real-time combined 2d+3d active appearance models. In CVPR, volume 2, pages 535 – 542, June 2004. | |
J.Q. Liu, Q. Z. Fan. “Research of feature extraction method on Facial Expression change”,Advanced Materials Research, Vol. 211-12, pp. 813-817, Feb. 2011. | |
L. Thai, N. Nguyen and T. Son. “A Facial Expression Classification System Integrating Canny, Principal Component Analysis and Artificial Neural Network” International Journal of Machine Learning and Computing, Vol. 1, No. 4, pp. 388-393, Oct. 2011. | |
L. Wiskott, J. M. Fellous, N. Kruger and C. von der Malsburg, Face recognition by elastic bunch graph matching, IEEE Trans. Patt. Anal. Mach. Intell. 19 (1997) 775{779.April 29,2004 13:49 WSPC/115-IJPRAI 00322. | |
Lee, R.S.T., “iJADE Authenticator- An Intelligent Multiagent based Facial Authentication System”, International Journal of Pattern Recognition and Artificial Intelligence, Vol.16, No.4: 481-500, 2002. | |
M. Bartlett, G. C. Littlewort , M. Frank, C Lainscsek, I. Fasel, J Movellan. “Automatic Recognition of facial actions in spontaneous expressions”, Journal of Multimedia, Vol. 1,No.6, Sept. 2006. | |
M. Leon, J. Rothkrantz. “Facial Action Recognition for Facial Expression Analysis from static face Images”, IEEE Transactions on System and Cybernetics, Vol. 34, No. 3, pp. 1449-1461, Jun. 2004. | |
M. S. Barlett et al. "Recognizing facial expression: machine learning and application to spontaneous behavior", IEEE Computer Society Conf. on Computer Vision and Pattern Recognition, 2005, pp. 568-573. | |
M. S. Barlett et al. "Recognizing facial expression: machine learning and application to spontaneous behavior", IEEE Computer Society Conf. on Computer Vision and Pattern Recognition, 2005, pp. 568-573. | |
M. Yeasin, B. Bullot, and R. Sharma. “Recognition of Facial Expressions and Measurement of Levels of Interest from video”, IEEE Transactions on Multimedia, Vol.8, No.3, pp. 500-508 Jun 2006. | |
Mehrabian, A., “Silent Messages”, Wadsworth, Belmont, California, 1971. | |
P Yang, Q. Liu, D. Metaxas. “Boosting Encoded dynamic features for facial Expression recognition”, Pattern Recognition Letters, Vol. 30, pp. 132-139, Jan 2009. | |
P. Aleksic and A. Katsaggelos. “Automatic Facial Expression Recognition using Facial Animation Parameters and Multi-Stream HMMs”, IEEE Tran. on Information Forensics and Security, Vol. 1, Issue 1, pp. 3-11, Mar. 2006. | |
P. Ekman and W. V. Friesen. “Facial Action Coding System”, Consulting Psychologists Press Inc., 577 College Avenue, Palo Alto, California 94306, 1978. | |
P. Sharma, “Feature Based Method for Human Facial Emotion Detection using optical Flow Based Analysis”, International Journal of Research in Computer Science, Vol. 1, Issue 1, pp.31-38, 2011. | |
R. S. Smith, T. Windeatt.“ Facial Expression Detection using Filtered Local Binary Pattern Features with ECOC Classifiers and Platt Scaling“, JMLR: Workshop and Conference Proceedings 11, 2010, pp.111-118. | |
Rowley, H., Baluja, S., and Kanade, T. 1998. Neural network-based face detection. IEEE Patt. Anal. Mach. Intell., 20:22–38. | |
S. Bashyal and G. Venayagamoorthy. “Recognizing facial expressions using gabor wavelets and vector quantization”, Engineering Application of Artificial Intelligence, Vol. 21, 2008. | |
S. Koelstra, M. Pantic and I. Patras. “A Dynamic Texture-Based Approach to Recognition of Facial Actions and Their Temporal Models”, IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol. 32, No. 11, pp. 1940-1954, Nov. 2010. | |
S. Lucey, A. Ashraf, and J. Cohn. “Investigating Spontaneous Facial Action Recognition through AAM Representations of the Face,” Face Recognition, K. Delac and M. Grgic, eds.,I-Tech Education and Publishing, 2007, pp. 275-286. | |
Sirakaya E. and Sonmez S., “Gender Images in State Tourism Brouchures: An Overlooked Area in Socially Responsible Tourism Marketing”, Journal of Travel Research, Vol. 38 (May):353-362, 2000. | |
Y. Tong, Y. Wang, Z. Zhu, J. Qiang. “Robust Facial Feature Tracking under varying face pose and facial expression”, Pattern Recognition, Vol. 40, pp. 3195-3208, 2007. | |
Yuasa, M., Yasumura, Y. and Nitta, K., “A Negotiation Support Tool Using Emotional Factors”, IEEE, Vol. 5: 2906-2911, 2001. | |
Yunfeng Zhu, Fernando De la Torre, Jeffrey F. Cohn, Associate Member, IEEE,and Yu-Jin Zhang, Senior Member, IEEE”Dynamic Cascades with Bidirectional Bootstrapping for Action Unit Detection in Spontaneous Facial Behavior”, Journal of LATEX Class Files, October 2010 | |
Mr. Archana Verma
C.C.E.T. Bhilai - India
archana.ver2k@gmail.com
Mr. Lokesh Kumar Sharma
National Institute of Occupational Health Ahmedabad, 380016, India - India
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