Facial Expression Recognition: A Survey

----------------------------------------------------------------***-----------------------------------------------------------------Abstract The automatic Facial Expression Recognition has been one of the latest research topic since 1990's. Face Expression plays an important role in human communication. This paper presents a high-level overview of automatic expression recognition; it highlights the main system components and some research challenges like variation in the illumination ,head pose and occlusion. Facial Expression Recognition is process performed by computer which consist of detect the face in the image and pre-process the face region, extracting facial features from image by analyzing the motion of facial features or change in the appearance of facial features and classifying this information into facial expression categories like facial action coding system or prototypic facial expression.

[1]  Shiqing Zhang,et al.  Facial expression recognition based on local binary patterns and local fisher discriminant analysis , 2012 .

[2]  G. Josemin Bala,et al.  A comparative study on ICA and LPP based Face Recognition under varying illuminations and facial expressions , 2013, 2013 International Conference on Signal Processing , Image Processing & Pattern Recognition.

[3]  P Dulguerov,et al.  Review of objective topographic facial nerve evaluation methods. , 1999, The American journal of otology.

[4]  Ioannis Pitas,et al.  An analysis of facial expression recognition under partial facial image occlusion , 2008, Image Vis. Comput..

[5]  KamleshLakhwani Shubhlakshmi Agrwal ShilpaChoudhary.  An Efficient Hybrid Technique Of Feature Extraction For Facial Expression Recognition Using Adaboost Classifier , 2012 .

[6]  Katherine B. Martin,et al.  Facial Action Coding System , 2015 .

[7]  Norbert Krüger,et al.  Face recognition by elastic bunch graph matching , 1997, Proceedings of International Conference on Image Processing.

[8]  Anil K. Jain,et al.  Statistical Pattern Recognition: A Review , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[9]  Markus Flierl,et al.  Graph-Preserving Sparse Nonnegative Matrix Factorization With Application to Facial Expression Recognition , 2011, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[10]  Dong Li,et al.  New research advances of facial expression recognition , 2009, 2009 International Conference on Machine Learning and Cybernetics.

[11]  Vijay Kumar,et al.  Facial Expression Recognition Using DCT, Gabor and Wavelet Feature Extraction Techniques , 2012 .

[12]  Kai-Tai Song,et al.  Facial expression recognition under illumination variation , 2007, 2007 IEEE Workshop on Advanced Robotics and Its Social Impacts.

[13]  P. Ekman.  Emotion in the human face , 1982 .

[14]  Timothy F. Cootes,et al.  Active Shape Models-Their Training and Application , 1995, Comput. Vis. Image Underst..

[15]  Takeo Kanade,et al.  Feature-point tracking by optical flow discriminates subtle differences in facial expression , 1998, Proceedings Third IEEE International Conference on Automatic Face and Gesture Recognition.

[16]  Marian Stewart Bartlett,et al.  Classifying Facial Actions , 1999, IEEE Trans. Pattern Anal. Mach. Intell..

[17]  Timothy F. Cootes,et al.  Active Appearance Models , 1998, ECCV.

[18]  Maja Pantic,et al.  Automatic Analysis of Facial Expressions: The State of the Art , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[19]  Beat Fasel,et al.  Automati Fa ial Expression Analysis: A Survey , 1999 .

[20]  Jörn Ostermann,et al.  Animation of synthetic faces in MPEG-4 , 1998, Proceedings Computer Animation '98 (Cat. No.98EX169).

[21]  Yegui Xiao,et al.  A New Facial Expression Recognition Technique using 2-D DCT and Neural Networks Based Decision Tree , 2006, The 2006 IEEE International Joint Conference on Neural Network Proceedings.

[22]  Franck Davoine,et al.  A solution for facial expression representation and recognition , 2002, Signal Process. Image Commun..

[23]  Meng Joo Er,et al.  Illumination compensation and normalization for robust face recognition using discrete cosine transform in logarithm domain , 2006, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[24]  Senthil Ragavan Valayapalayam Kittusamy,et al.  Facial Expressions Recognition Using Eigenspaces , 2012 .

[25]  Shaogang Gong,et al.  Facial expression recognition based on Local Binary Patterns: A comprehensive study , 2009, Image Vis. Comput..

[26]  S. Lajevardi,et al.  Novel higher-order local autocorrelation-like feature extraction methodology for facial expression recognition , 2010 .

[27]  Liyiiig Miit.  A NEW FACIAL EXPRESSION RECOGNITION TECHNIQUE USING 2-D DCT AND K-MEANS ALGORITHM , 2004 .

[28]  Lianwen Jin,et al.  A New Facial Expression Recognition Method Based on Local Gabor Filter Bank and PCA plus LDA , 2006 .

[29]  Yau-Hwang Kuo,et al.  Emotion recognition based on a novel triangular facial feature extraction method , 2010, The 2010 International Joint Conference on Neural Networks (IJCNN).

[30]  Timothy F. Cootes,et al.  Face Recognition Using Active Appearance Models , 1998, ECCV.