Facial Expression Recognition: A Literature Survey
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International Journal of Computer Trends and Technology (IJCTT) |  |
| © 2017 by IJCTT Journal | ||
| Volume-48 Number-1 |
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| Year of Publication : 2017 | ||
| Authors : Mrs. Jyothi S Nayak, Preeti G, ManishaVatsa, Manisha Reddy Kadiri, Samiksha S | ||
| DOI : 10.14445/22312803/IJCTT-V48P101 |
Mrs. Jyothi S Nayak, Preeti G, ManishaVatsa, Manisha Reddy Kadiri, Samiksha S "Facial Expression Recognition: A Literature Survey". International Journal of Computer Trends and Technology (IJCTT) V48(1):1-4, June 2017. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.
Abstract -
Facial expression recognition is becoming increasingly popular because of the need for human machine interaction. The recognition of facial expressions is not an easy problem for machine learning methods, since different people can vary in the way that they show their expressions. And even an image of the same person in one expression can vary in brightness, background and position. We conducted an extensive literature survey to compare the efficiencies of the various facial expression recognition techniques. The two popular databases used in most techniques are: 1) Cohn-Kanade AU-coded database and 2) JAFFE database. This paper aims at identifying the techniques used for the recognition of the six basic expressions: Joy, neutral, anger, sad, surprise and disgust.
References
[1] Mohammad Soleymani, Member, IEEE, SadjadAsghari-Esfeden, Student member, IEEE Yun Fu, Senior Member, IEEE, MajaPantic, Fellow, IEEE, “Analysis of EEG signals and facial expressions for continuous emotion detection” IEEE Transactions on Affective Computing, volume 7, Issue :1, pg 17- 28, March 2016
[2]NirvairNeeru and Dr. LakhwinderKaur, “Face Recognition based on LBP and CS-LBP Technique under Different Emotions” Computational Intelligence and Computing Research(ICCIC), 2015 IEEE International Conference, Dec 2015.
[3] G. Tharshini, H. G. C. P. Dinesh, G. M. R. I. Godaliyadda and M. P. B. Ekanayake, “A Robust Expression Negation Algorithm for Accurate Face Recognition for Limited Training Data” ,Industrial and Information Systems(ICIIS), 2015 IEEE 10TH International Conference, Dec 2015.
[4]AdvaitApte, ArshithaBasavaraj and Nithin R “Efficient Facial Expression Recognition and Classification System based on Morphological Processing of Frontal Face Images”, Industrial and Information Systems (ICIIS), 2015 IEEE 10TH International Conference, Dec 2015.
[5] Y. Yoshitomi, N. Miyawaki, S. Tomita and S. Kimura, “Facial Expression Recognition Using Thermal Image Processing and Neural Network”, Robot and Human Communication, 6th IEEE International Workshop, Oct 1997.
[6] Austin Nicolai and Anthony Cho, “Facial Emotion Recognition Using Fuzzy Systems”, Systems, Man, and Cybernetics (SMC), 2015 IEEE International Conference, Oct 2015.
[7]Devadethan. S, Geevarghese Titus and Purushothaman S “Face Detection and Facial Feature Extraction Based on a Fusion of Knowledge Based Method and Morphological Image Processing”, Emerging Research Areas: Magnetics, Machine and Drives (AICERA/iCMMD),2014 Annual International Conference, July 2014.
[8]MeshiaC´edricOveneke, Isabel Gonzalez, Weiyi Wang, Dongmei Jiang, and HichemSahli, “Monocular 3D, Facial Information Retrieval for Automated Facial Expression Analysis”, Affective Computing and Intelligent Interaction (ACII), 2015 IEEE International Conference, Sept. 2015.
[9] Human Face Recognition through Moment Descriptors Geetika Singh and InduChhabra, “Human Face Recognition through Moment Descriptors”, Engineering and Computational Sciences (RAECS), 2014 Recent Advances, March 2014.
[10] Sánchez, A.B. Moreno, J.F. Vélez, “Recognizing Intensity Degrees from Expressions in 3D Facial Meshes”, Systems, Signals and Image Processing (IWSSIP), 2013 20th International Conference, July 2013.
[11]ShiladityaChowdhury, AniruddhaDey, JamunaKanta Sing, Dipak Kumar Basu, MitaNasipuri, “A Novel Elastic Window for Face Detection and Recognition from Video”, Computational Intelligence and Communication Networks (CICN), 2014 International Conference, Nov 2014.
[12]Anusha V upputuri, SukadevMeher, “Facial Expression Recognition using Local BinaryPatterns and KullbackLeibler Divergence” Communication and Signal Processing (ICCSP), 2015 International Conference, April 2015
[13]M Sorci, G Antonini and Jean PhilipeThiran, Signal Processing Institute, “Fisher`s discriminant and component analysis for static facial expression classification” Signal Processing Conference , 2007 15th European Sept 2007.
[14]Sabu, Mr. Paul P Mathai, Elsa Sabu, “An extensive review of facial expression recognition using salient facial patches”, Applied and Theoretical Computing and Communication Technology (iCATccT), 2015 International Conference ,Oct 2015.
[15]Md Zia Uddin, “Facial expression recognition using Depth Information and Spatiotemporal features”, Advance Communication Technology (ICACT), 2016 18th International Cinference, Feb 2016.
[16] Riddhi Patel, Shruti B Yagnik, “A literature survey on face recognition techniques”, International Journal of Computer Trends and Technology, Nov 2013.
[17] Ms.Drashti H. Bhatt, Mr.Kirit R. Rathod, Mr.Shardul J. Agravat, “ A study of local binary pattern method for facial expression detection”, International Journal of Computer Trends and Technology, Feb 2014. [18] SapnaVishwakarma, Prof Krishan Kant Pathak, “Face recognition using LBP Coefficient Vectors with SVM Classifier”, International Journal of Computer Trends and Technology, Mar 2014.
Keywords
Face detection, facial expressions, expression recognitions, expression classification, datasets.