Full text

Turn on search term navigation

© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.

Abstract

Costume restoration is one of the important ways to study costume history and culture. The purpose of this paper is to show the characteristics of Chinese costumes more than 1000 years ago, through the research on the costume in the famous ancient Chinese painting DaoLian painting, and provide strong technical support for the research of Chinese ancient costume culture. DaoLian painting is the work of Xuan Zhang, a famous painter in Tang dynasty (618–907), China. From the perspective of clothing engineering, we analyzed the characteristics of costume style, color, and pattern and used the virtual fitting technology to realize digital restoration of the costume of 12 characters in the painting. The results show that it is a practical method to study costume from paintings. The colors, patterns, and character gestures in the paintings provide sufficient information for the archaeology and restoration of ancient costumes. The research results of this paper can provide a new idea for costume archaeology and a reference for modern fashion design and materials for the VR Museum of Ancient Costumes.

Details

Title
Research on Archaeology and Digital Restoration of Costumes in DaoLian Painting
Author
Zhu, Chun 1 ; Liu, Kaixuan 2 ; Li, Xiaoning 3 ; Zeng, Qingwei 3 ; Wang, Ruolin 3 ; Zhang, Bin 3 ; Zhao Lü 3 ; Chen, Chen 3 ; Xin, Xiaoyu 4 ; Wu, Yunlong 5 ; Zhang, Junjie 6 ; Zeng, Xianyi 7   VIAFID ORCID Logo 

 School of Fashion and Art Design, Xi’an Polytechnic University, Xi’an 710048, China; GEMTEX Laboratory, Ecole Nationale Superieure des Arts et Industries Textiles, 59056 Roubaix, France; Fashion and Art Design Institute, Donghua University, Shanghai 200051, China 
 School of Fashion and Art Design, Xi’an Polytechnic University, Xi’an 710048, China; GEMTEX Laboratory, Ecole Nationale Superieure des Arts et Industries Textiles, 59056 Roubaix, France 
 School of Fashion and Art Design, Xi’an Polytechnic University, Xi’an 710048, China 
 College of Textile and Clothing, Xinjiang University, Urumqi 830017, China 
 School of Materials Science & Engineering, Xi’an Polytechnic University, Xi’an 710048, China 
 School of Computer Science and Artificial Intelligence, Wuhan Textile University, Wuhan 430200, China 
 GEMTEX Laboratory, Ecole Nationale Superieure des Arts et Industries Textiles, 59056 Roubaix, France 
First page
14054
Publication year
2022
Publication date
2022
Publisher
MDPI AG
e-ISSN
20711050
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2769914400
Copyright
© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.