Abstract
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.
Highlights
In order to contribute to the theory of cultural specificity of basic expressions of emotions, from a composite viewpoint of psychology and Human-Computer Interaction (HCI), this paper presents a methodical analysis of Western-Caucasian and East-Asian prototypic facial expressions based on four specific facial regions: forehead, eyes-eyebrows, mouth and nose
A total of 656 images were used for this paper. 480 expressive and 176 neutral facial images were selected from four standard datasets which were divided into two racial groups, representing three possible training sets: Western-Caucasian dataset (WSN), East-Asian (ASN) dataset and the multicultural dataset (MUL)
ASN dataset contains 326 images selected from 86 subjects(47% males) of three different datasets: Japanese Female Facial Expression (JAFFE) dataset [28], which comprises 213 images of 10 Japanese female models; Japanese and Caucasian Facial Expression of Emotion (JACFEE) dataset [29], which contains 56 images from different individuals including 28 Japanese and 28 Caucasian subjects; and Taiwanese Facial Expression Image Database (TFEID) [30], which includes 336 images from 40 Taiwanese models
Summary
Since the early work of Charles Darwin [1], facial expressions have been considered as a universal language, which can be recognized across different races and cultures around the world. EMFACS focuses on muscle movements called Action Units (AUs), which are related to the six basic emotions, and it provides specific coding for each of them. A certain part of the research community has promoted an opposite theory of the universality hypothesis. They proposed that the facial expressions are based on cultural learning and different races may have different ways to express emotions [4]. Recent cross-cultural studies have to some degree refuted this assumed universality by finding differences on facial expressions of WesternCaucasian and East-Asian people [5] [6]
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