Computer Science ›› 2016, Vol. 43 ›› Issue (Z11): 123-126.doi: 10.11896/j.issn.1002-137X.2016.11A.026

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Research Advance of Facial Expression Recognition

HUANG Jian, LI Wen-shu and GAO Yu-juan   

  • Online:2018-12-01 Published:2018-12-01

Abstract: Facial expression recognition (FER) is an active research topic in the fields of computer vision,machine learning and artificial intelligence,and has become a hot research.In this paper,we introduced the FER system processes,summarized the common method of facial expression feature extraction and facial expression classification,as well as the improvement of these methods proposed by domestic and foreign scholars in recent years,and compared the advantages and disadvantages of these methods.Finally,the current difficult problems of FER studies were analyzed,and the future development direction of FER was presented.

Key words: Facial expression recognition,Facial expression feature extraction,Facial expression classification

[1] Ojala T,Pietikinen M,Harwood D.A comparative study of texture measures with classification based on featured distributions [J].Pattern Recognition,1996,9(1):51-59
[2] Guo Z,Zhang D.A completed modeling of local binary pattern operator for texture classification [J].IEEE Transactions on Image Processing,2010,19(6):1657-1663
[3] Guo Y,Zhao G,Pietikinen M.Discriminative features for texture description [J].Pattern Recognition,2012,45(10):3834-3843
[4] 周宇旋,吴秦,梁久祯,等.判别性完全局部二值模式人脸表情识别[J/OL].计算机工程与应用,
[5] Gabor D.Theory of communications.IEEE Journal of the Institution of Electrical Engineers-Part III[J].Radio and Communication Engineers,1946,93(26):429-457
[6] Liu Shuai-shi,Tian Yan-tao,Wan Chuan.Facial Expression Re-cognition Method Based on Gabor Multi-orientation Features Fusion and Block Histogram [J].Acta Automatica Sinica,2011,37(12):1455-1463
[7] 钟思志.人脸面部表情识别算法研究[J].上海:华东师范大学,2015
[8] Cootes T,Taylor C,Cooper D,et al.Active shape models-their training and application [J].Computer Vision and lmage Understanding,1995,61(1):38-59
[9] Peng Cheng,Liu Shuai-shi,Wan Chuan.An active shape model for facial expression recognitionbased on a local texture model[J].CAAI Transactions on Intelligent Systems,2011,6(3)
[10] 侯婕.人脸表情计算技术研究[D].苏州:苏州大学,2014
[11] Edwards G,Taylor C,Cootes T.Interpreting face images using active appearance models [C]∥Automatic Face and Gesture Recognition.1998:300-305
[12] Saatci Y.Town C.Cascaded Classification of Gender and Facial Expression using Active Appearance Models[C]∥Proceedings of the 7th International Conference on Automatic Face and Gesture Recognition.2006:393-398
[13] Lowe D G.Object recognition from local scale-invariant features[C]∥International Conference on Computer Vision.Greeee:Kerkyra,1999:1150-1157
[14] Lowe D G.Distinctive image features from scale-invariant keypoints[J].International journal of Computer Vision,2004,0(2):91-110
[15] Berretti S,Bimbo A D,Pala P,et al.A set of selected SIFT features for 3D facial expression recognition[C]∥20th lnternatio-nal Conference on Pattern Recognition (ICPR).2010:4125-4128
[16] 蔡乐毅.基于主动形状模型的人脸识别算法的研究[D].杭州:浙江工业大学,2013
[17] Ren Fu-ji,Huang Zhong.Facial Expression Recognition Based on AAM-SIFT and Adaptive Regional Weighting [J].IEEJ Transactions on Electrical and Electronic Engineering,2015,0:713-722
[18] Yacoob Y,Davis L.Recognizing Human Facial Expressions from Long Image Sequences Using Optical Flow [J].IEEE Transactions on Pattern Analysis and Machine Intelligence,1996,8(6):636-642
[19] Brox T,Bruhn A,Papenberg N,et al.High Accuracy OpticalFlow Estimation Based on a Theory For Warping[M].Berlin:Spring Berlin Heidelberg,2004:25-36
[20] Papenberg N,Bruhn A,Brox T,et al.Highly accurate optic flow computation with theoretically justified warping [J].Inter.J.Computer Vision,2006,7(2):141-158
[21] 何俊,蔡建锋,房灵芝,等.基于LBP/VAR与DBN模型的人脸表情识别[J].计算机应用研究,2016,33(8):2509-2513
[22] 苟佳丽.基于视频的人脸表情识别技术研究 [D].成都:西南交通大学,2014
[23] Tie Y,Guan L.A deformable 3D facial expression model for dynamic human emotional state recognition[J].IEEE Transactions on Circuits and Systemsfor Video Technoloy,2013,23 (1):142-157
[24] Tslakanidou F,Malassiotis S.Real-time 2D+3D facial actionand expression recognition [J].Pattern Recognition,2010,43(6):1763-177
[25] Ying Zi-lu,Tang Jing-hai,Li Jing-wen,et al.Support vector discriminant analysis and its application to facial expression recognition[J].Acta Electronica Sinica,2008,36(4):725-730
[26] Radulovic J,Rankovic V.Feedforward neural network and adaptive network-based fuzzy inference system in study of power lines[J].Expert Systems with Applications,2010,37(1):165-70
[27] Wang Zhan,Ruan Qiu-qi,An Guo-yun.Facial expression recognition based on tensor local linear discriminant analysis[C]∥IEEE 11th International Conference on Signal Processing.Beijing,2012:1226-1229
[28] Mclvor R T,Humphreys P K.A case-based reasoning approach to the make or buy decision[J].Integrated Manufacturing Systems,2000(5):295-310
[29] Zhao X,Zhang S.Facial expression recognition using local binary patterns and discriminant kernel locally linear embedding[J].EURASIP Journal on Advances in Signal Processing,2012(1):1-9
[30] Vasilescu M A O,Terzopoulos D.Multilinear analysis of image ensembles:tensor faces[J].ECCV,2002(1):447-460
[31] Wang H,Ahuja N.Facial expression decomposition[C]∥International Conference on Computer Vision.2003:958-965
[32] Zhu Ming-han,Luo Da-yong.Expression decomposition algo-rithm based on appearance manifolds [J].Computer Engineering and Applications,2008,44(23):203-205
[33] Cortes C,Vapnik V.Support-Vector Networks [J].Machine Learning,1995,20(3):273-297
[34] 王文成.基于局部特征分析的人脸表情识别问题研究[D].济南:山东大学:2011
[35] Zhan Y Z,Cheng K Y,Chen Y B,et al.A New Classifier for Facial Expression Recognition:Fuzzy Buried Markov Model [J].Journal of Computer Science and Technology,2010,25(3):641-650
[36] 王剑云,李小霞.一种基于深度学习的表情识别方法[J].计算机与现代化,2015(1):84-87
[37] 徐文晖,孙正兴.面向视频序列表情分类的LSVM算法[J].计算机辅助设计与图形学学报,2009,21(4):542-548
[38] Wang Xiao-hu,Liu An,Zhang Shi-qing.New facial expressionrecognition based on FSVM and KNN [J].Optik,2015(126):3132-3134

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