Study on Face Classification and Modeling Based on the Fit Problem of Respirator for Chinese Adults

DOI

10.2991/ammsa-18.2018.43How to use a DOI?

Keywords

mask; head-face measurements; facial classification; reverse modeling

Abstract

To solve the fit problem between the face and the mask in the market, 7 facial indexes related facial masks of 194 adults were measured in this paper. Factor analysis was undertaken and two main factors were chosen. Through counting the relative index, 3 representative body indexes were selected as clustering variables. K-means cluster was applied to classify the figure type and the optimal number of clusters was determined by Mix-F statistics. Combined with reverse engineering design software, the model was established by using the object of the clustering center value of each index in the class 5 standard face. This study provides practical guidance for the forward design and production of the follow-up mask. The multi-surface modeling of human face has broadened the new thinking to deal with the contradiction between clothing and body.

Copyright

© 2018, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Xiaotong Zhou
AU  - Xiaoxia Song
PY  - 2018/05
DA  - 2018/05
TI  - Study on Face Classification and Modeling Based on the Fit Problem of Respirator for Chinese Adults
BT  - Proceedings of the 2018 2nd International Conference on Applied Mathematics, Modelling and Statistics Application (AMMSA 2018)
PB  - Atlantis Press
SP  - 211
EP  - 214
SN  - 1951-6851
UR  - https://doi.org/10.2991/ammsa-18.2018.43
DO  - 10.2991/ammsa-18.2018.43
ID  - Zhou2018/05
ER  -