A Brief Review of Facial Expressions Recognition System

  • Devashree Joshi


A wide range of applications exist for Facial Expression Recognition (FER) like neutral, sadness, surprise, happiness, fear, anger, contempt and disgust, which include Emotional / Mental state recognition, stress and anxiety detection in medial domain,  security domain, human computer interaction etc. In computer vision field Facial Expression Recognition is very interesting and challenging area. In this paper, review some of the facial expression recognition methods are presented. The feature extraction techniques play a crucial role. In this paper a few Facial Feature Extraction techniques like Local Binary Pattern, Local Directional Pattern are discussed. Also recognition based on support vector machines and deep learning algorithms are discussed and compared.   

Keywords: facial emotion recognition, deep learning based FER, LBP, LDP.


[1] Jyoti Kumari, R.Rajesh, KM.Pooja, “Facial expression recognition: A survey”, ELSEVIER, Second International Symposium on Computer Vision and the Internet(2015 ) 486 – 491.
[2] Hamed Monkaresi, Nigel Bosch, Rafael A. Calvo, “Automated Detection of Engagement Using Video-Based Estimation of Facial Expressions and Heart Rate”, IEEE Transactions On Affective Computing, Vol. 8, No. 1, January-March 2017.
[3] Veena Mayya, Radhika M. Pai, Manohara Pai M. M., “Automatic Facial Expression Recognition Using DCNN”,ELSEVIER Procedia Computer Science 93 ( 2016 ) 453 – 461.
[4] Ghulam Muhammad, Mansour Alsulaiman, “A Facial-Expression Monitoring System for Improved Healthcare in Smart Cities”, IEEE Access, Special Section On Advances Of Multisensory Services And Technologies For Healthcare In Smart Cities, date of publication June 7, 2017.
[5] Ankit Goyal, Naveen Kumar, Tanaya Guha, “A Multimodal Mixture-Of-Experts Model For Dynamic Emotion Prediction In Movies “,Acoustics, Speech and Signal Processing (ICASSP), 2016 IEEE International Conference , DOI: 10.1109/ICASSP.2016.7472192.
[6] Yoann Baveye, Emmanuel Dellandr´ea, Christel Chamaret and Liming Chen, “Deep Learning vs. Kernel Methods: Performance for Emotion Prediction in Videos”, 2015 International Conference on Affective Computing and Intelligent Interaction (ACII), 978-1-4799-9953-8/15/$31.00 ©2015 IEEE.
[7] Viraj Mavani, Shanmuganathan Raman, Krishna P Miyapuram, “Facial Expression Recognition using Visual Saliency and Deep Learning”, Journal Computer Vision and Pattern Recognition (cs.CV) 26 Aug 2017.
[8] Md. Hasanul Kabir, Md Sirajus Salekin, Md. Zia Uddin, And M. Abdullah-Al-Wadud, “Facial Expression Recognition From Depth Video With Patterns of Oriented Motion Flow”, IEEE Access, DOI 10.1109/ACCESS.2017.2704087 May 16, 2017.
[9] Jiaxing Lia, Dexiang Zhanga, Jingjing Zhanga, Jun Zhanga, Teng Lia, Yi Xiaa, Qing Yana, and Lina Xuna, “Facial Expression Recognition with Faster R-CNN”, ELSEVIER Procedia Computer Science 107 ( 2017 ) 135 – 140.
[10] Gibran Benitez-Garcia Tomoaki Nakamura Masahide Kaneko, “Analysis of In- and Out-group Differences between Western and East-Asian Facial Expression Recognition”, 2017 Fifteenth IAPR International Conference on Machine Vision Applications (MVA) Nagoya University, Nagoya, Japan, May 8-12, 2017.
[11] Jadisha Yarif Ram´ırez Cornejo, Helio Pedrini, “Recognition Of Occluded Facial Expressions Based On Centrist Features”, Acoustics, Speech and Signal Processing (ICASSP), 2016 IEEE International Conference , DOI: 10.1109/ICASSP.2016.7471886
[12] Abdelwahab Bourai, Tadas Baltrušaitis, Louis-Philippe Morency, “Automatically Predicting Human Knowledgeability through Non-verbal Cues “,Proceedings of the 19th ACM International Conference on Multimodal Interaction, ISBN: 978-1-4503-5543-8, 2017.
[13] Husam Salih, Lalit Kulkarni, “Study of Video based Facial Expression and Emotions Recognition Methods”, International conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), 2017.
[14] G. Giannakakisa, M. Pediaditisa, D. Manousosa, E. Kazantzakia, F. Chiarugia,P.G. Simosb,a, K. Mariasa, M. Tsiknakisa, “Stress and anxiety detection using facial cues from videos”, ELSEVIER journal of Biomedical Signal Processing and Control 2017.
[15] Panagiotis Tzirakis , George Trigeorgis , Mihalis A. Nicolaou, Bj¨orn W. Schuller, and Stefanos Zafeiriou, “End-to-End Multimodal Emotion Recognition Using Deep Neural Networks”, IEEE Journal Of Selected Topics In Signal Processing, Vol. 11, No. 8, December 2017.
[16] Madhumita Takalkar, Min Xu, Qiang Wu & Zenon Chaczko, “A survey: facial micro-expression recognition”, Springer Science+Business Media, LLC 2017, doi.org/10.1007/s11042-017-5317-2.
[17] Kanade, T., Cohn, J. F., & Tian, Y. (2000). Comprehensive database for facial expression analysis. Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition (FG'00), Grenoble, France, 46-53.
[18] Lucey, P., Cohn, J. F., Kanade, T., Saragih, J., Ambadar, Z., & Matthews, I. (2010). The Extended Cohn-Kanade Dataset (CK+): A complete expression dataset for action unit and emotion-specified expression. Proceedings of the Third International Workshop on CVPR for Human Communicative Behavior Analysis (CVPR4HB 2010), San Francisco, USA, 94-101.
[19] M.F. Valstar, M. Pantic, “ Induced Disgust, Happiness and Surprise: an Addition to the MMI Facial Expression Database ”, Proceedings of the International Language Resources and Evaluation Conference, Malta, May 2010.
[20] M. Pantic, M.F. Valstar, R. Rademaker and L. Maat, “ Web­based database for facial expression analysis ”, Proc. IEEE Int'l Conf. on Multimedia and Expo (ICME'05), Amsterdam, The Netherlands, July 2005.
[21] Michael J. Lyons, Shigeru Akamatsu, Miyuki Kamachi & Jiro Gyoba , “Coding Facial Expressions with Gabor Wavelets”, Proceedings, Third IEEE International Conference on Automatic Face and Gesture Recognition, April 14-16 1998, Nara Japan, IEEE Computer Society, pp. 200-205.
[22] Dong –Ju Kim*, Sang-Heon, “Face Recognition via Local Directional Pattern, International Journal of Security and Its Applications 2013.
[23] Byoung Chul Ko , “A Brief Review of Facial Emotion Recognition Based on Visual Information”, sensors, 2018.
213 Views | 149 Downloads
How to Cite
Joshi, D. (2018). A Brief Review of Facial Expressions Recognition System. Asian Journal For Convergence In Technology (Founded by ISB &M School of Technology )), 4(I). https://doi.org/10.33130/asian journals.v4iI.388