Methodical Analysis of Western-Caucasian and East-Asian Basic Facial Expressions of Emotions Based on Specific Facial Regions

Facial expressions are the straight link for showing human emotions. Psychologists have established the universality of six prototypic basic facial expressions of emotions which they believe are consistent among cultures and races. However, some recent cross-cultural studies have questioned and to some degree refuted this cultural universality. Therefore, in order to contribute to the theory of cultural specificity of basic expressions, from a composite viewpoint of psychology and HCI (Human Computer Interaction), this paper presents a methodical analysis of Western-Caucasian and East-Asian prototypic expressions focused on four facial regions: forehead, eyes-eyebrows, mouth and nose. Our analysis is based on facial expression recognition and visual analysis of facial expression images of two datasets composed by four standard databases CK+, JAFFE, TFEID and JACFEE. A hybrid feature extraction method based on Fourier coefficients is proposed for the recognition analysis. In addition, we present a cross-cultural human study applied to 40 subjects as a baseline, as well as one comparison of facial expression recognition performance between the previous cross-cultural tests from the literature. With this work, it is possible to clarify the prior considerations for working with multicultural facial expression recognition and contribute to identifying the specific facial expression differences between Western-Caucasian and East-Asian basic expressions of emotions.

[1]  Tomoaki Nakamura,et al.  Analysis of differences between Western and East-Asian faces based on facial region segmentation and PCA for facial expression recognition , 2017 .

[2]  P. Ekman Universals and cultural differences in facial expressions of emotion. , 1972 .

[3]  Tae-Sun Choi,et al.  Boosted NNE collections for multicultural facial expression recognition , 2016, Pattern Recognit..

[4]  P. Ekman,et al.  Facial action coding system , 2019 .

[5]  Masahide Kaneko,et al.  Analysis of in- and out-group differences between Western and East-Asian facial expression recognition , 2017, 2017 Fifteenth IAPR International Conference on Machine Vision Applications (MVA).

[6]  Y. V. Venkatesh,et al.  Facial expression recognition using radial encoding of local Gabor features and classifier synthesis , 2012, Pattern Recognit..

[7]  Manasi S. Patwardhan,et al.  Survey on real-time facial expression recognition techniques , 2016, IET Biom..

[8]  Michael J. Lyons,et al.  Coding facial expressions with Gabor wavelets , 1998, Proceedings Third IEEE International Conference on Automatic Face and Gesture Recognition.

[9]  Lijiang Chen,et al.  Facial expression recognition considering individual differences in facial structure and texture , 2014, IET Comput. Vis..

[10]  D. Sauter,et al.  Commonalities outweigh differences in the communication of emotions across human cultures [Letter to the editor] , 2013 .

[11]  Masahide Kaneko,et al.  Facial Expression Recognition Based on Facial Region Segmentation and Modal Value Approach , 2014, IEICE Trans. Inf. Syst..

[12]  Wonjun Hwang,et al.  Face Recognition System Using Multiple Face Model of Hybrid Fourier Feature Under Uncontrolled Illumination Variation , 2011, IEEE Transactions on Image Processing.

[13]  P. Ekman,et al.  Matsumoto and Ekman's Japanese and Caucasian Facial Expressions of Emotion (JACFEE): Reliability Data and Cross-National Differences , 1997 .

[14]  Andrea Cavallaro,et al.  Automatic Analysis of Facial Affect: A Survey of Registration, Representation, and Recognition , 2015, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[15]  Chih-Jen Lin,et al.  LIBSVM: A library for support vector machines , 2011, TIST.

[16]  Masahide Kaneko,et al.  顔部品の「Bag of Words」とPHOG記述子を用いた顔表情認識 , 2010 .

[17]  Takeo Kanade,et al.  Comprehensive database for facial expression analysis , 2000, Proceedings Fourth IEEE International Conference on Automatic Face and Gesture Recognition (Cat. No. PR00580).

[18]  Takeo Kanade,et al.  Facial Expression Recognition , 2011, Handbook of Face Recognition.

[19]  Mohammad Reza Mohammadi,et al.  PCA-based dictionary building for accurate facial expression recognition via sparse representation , 2014, J. Vis. Commun. Image Represent..

[20]  Alex Pentland,et al.  Face recognition using eigenfaces , 1991, Proceedings. 1991 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[21]  Oliver G. B. Garrod,et al.  Facial expressions of emotion are not culturally universal , 2012, Proceedings of the National Academy of Sciences.

[22]  Masahide Kaneko,et al.  Computerized Facial Caricatures , 2008 .

[23]  Michael J. Lyons,et al.  Evidence and a computational explanation of cultural differences in facial expression recognition. , 2010, Emotion.

[24]  Masahide Kaneko,et al.  Facial Expression Recognition Using Facial-component-based Bag of Words and PHOG Descriptors , 2010 .

[25]  Edilson de Aguiar,et al.  Facial expression recognition with Convolutional Neural Networks: Coping with few data and the training sample order , 2017, Pattern Recognit..

[26]  Rachael E. Jack Culture and facial expressions of emotion , 2013 .

[27]  Hélio Pedrini,et al.  Effects of cultural characteristics on building an emotion classifier through facial expression analysis , 2015, J. Electronic Imaging.

[28]  C. Darwin The Expression of the Emotions in Man and Animals , .

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

[30]  Hazem M. El-Bakry Automatic human face recognition using modular neural networks , 2001 .

[31]  Héctor M. Pérez Meana,et al.  A sub-block-based eigenphases algorithm with optimum sub-block size , 2013, Knowl. Based Syst..