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Application of Stereo Digital Image Correlation on Facial Expressions Sensing

Authors :
Xuanshi Cheng
Shibin Wang
Huixin Wei
Xin Sun
Lipan Xin
Linan Li
Chuanwei Li
Zhiyong Wang
Source :
Sensors, Vol 24, Iss 8, p 2450 (2024)
Publication Year :
2024
Publisher :
MDPI AG, 2024.

Abstract

Facial expression is an important way to reflect human emotions and it represents a dynamic deformation process. Analyzing facial movements is an effective means of understanding expressions. However, there is currently a lack of methods capable of analyzing the dynamic details of full-field deformation in expressions. In this paper, in order to enable effective dynamic analysis of expressions, a classic optical measuring method called stereo digital image correlation (stereo-DIC or 3D-DIC) is employed to analyze the deformation fields of facial expressions. The forming processes of six basic facial expressions of certain experimental subjects are analyzed through the displacement and strain fields calculated by 3D-DIC. The displacement fields of each expression exhibit strong consistency with the action units (AUs) defined by the classical Facial Action Coding System (FACS). Moreover, it is shown that the gradient of the displacement, i.e., the strain fields, offers special advantages in characterizing facial expressions due to their localized nature, effectively sensing the nuanced dynamics of facial movements. By processing extensive data, this study demonstrates two featured regions in six basic expressions, one where deformation begins and the other where deformation is most severe. Based on these two regions, the temporal evolutions of the six basic expressions are discussed. The presented investigations demonstrate the superior performance of 3D-DIC in the quantitative analysis of facial expressions. The proposed analytical strategy might have potential value in objectively characterizing human expressions based on quantitative measurement.

Details

Language :
English
ISSN :
14248220
Volume :
24
Issue :
8
Database :
Directory of Open Access Journals
Journal :
Sensors
Publication Type :
Academic Journal
Accession number :
edsdoj.6f112c43785848a39603a87f0180e2eb
Document Type :
article
Full Text :
https://doi.org/10.3390/s24082450