Computer Science and Information Technology Vol. 7(3), pp. 96 - 101
DOI: 10.13189/csit.2019.070305
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Study on Face Classification and Modeling Based on the Respirator-fit Problem for Chinese Adults

Xiaotong Zhou , Xiaoxia Song ^*
Fashion Institute, Shanghai University of Engineering Science, China

ABSTRACT

Introduction: In China, respirator is widely used to protect the public from air pollution. The design of respirator is based on anthropometric date obtained from groups of people in RFTPs (respirator fit test panels). Meanwhile the respirator-user fit is not satisfied as unsatisfactory seal exist. Methods: To solve the respirator-user fit problem in China, this study was divided into four parts: The public head-face measurement and analysis of head data clustering; reverse establishment of head model can be based on the clustering results; using the model, forward design of mask structure can be conducted. Results: Combined with Rotation component matrix counting and the relative index, 3 out of 7 representative facial indexes can be used as clustering variables. They are nose length, bitragion breadth and face height. The optimal number of clusters was 5 determined by Mix-F statistics. According to the methods of mathematical statistics, it shows that the main kind is short and narrow which is the fifth in this article. By using the plaster replica method based on the 3D print of the facial model, the chart pattern of optimized small-face mask was achieved.

KEYWORDS
Mask, Head-face Measurements, Facial Classification, Reverse Modeling

Cite This Paper in IEEE or APA Citation Styles
(a). IEEE Format:
[1] Xiaotong Zhou , Xiaoxia Song , "Study on Face Classification and Modeling Based on the Respirator-fit Problem for Chinese Adults," Computer Science and Information Technology, Vol. 7, No. 3, pp. 96 - 101, 2019. DOI: 10.13189/csit.2019.070305.

(b). APA Format:
Xiaotong Zhou , Xiaoxia Song (2019). Study on Face Classification and Modeling Based on the Respirator-fit Problem for Chinese Adults. Computer Science and Information Technology, 7(3), 96 - 101. DOI: 10.13189/csit.2019.070305.