Journal of Textile Research ›› 2020, Vol. 41 ›› Issue (12): 124-129.doi: 10.13475/j.fzxb.20200505006

• Apparel Engineering • Previous Articles     Next Articles

Automatic measurement of key dimensions for Han-style costumes based on use of convolutional neural network

WANG Yiwen1, LUO Ronglei2,3(), KANG Yuzhe4   

  1. 1. School of Fashion Design & Engineering, Zhejiang Sci-Tech University, Hangzhou, Zhejiang 310018, China
    2. School of International Education, Zhejiang Sci-Tech University, Hangzhou, Zhejiang 310018, China
    3. Silk and Fashion Culture Center, Hangzhou, Zhejiang 310018, China
    4. School of Information Science and Technology, Zhejiang Sci-Tech University, Hangzhou, Zhejiang 310018, China
  • Received:2020-05-26 Revised:2020-08-31 Online:2020-12-15 Published:2020-12-23
  • Contact: LUO Ronglei E-mail:luoronglei@163.com

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Abstract:

In order to quickly and accurately obtain the key dimensions of the ancient Chinese Han-style costumes with scarce sample data, a clothing size measurement scheme based on the use of convolutional neural network was proposed in this paper. Firstly, a two-stage convolutional neural network model GlobalNet-RefineNet was built for detecting the key points. The accuracy of the key point recognition was improved through twice transfer learning and repeated iterative training. An algorithm was used to get the pixel distance between coordinate points. Combined with the tiles of Han-style costume and at least one real measurement size given in the museum or excavation report, the size data of the whole garment were obtained through proportional mapping. This research used the top of a Han-style costume as an example for experiments. The research results show that after two times of transfer learning, the model has a high degree of convergence and good training effect. The relative error of costume top size measured by this scheme is between 0.59%-4.17%. This research provides new ideas for the restoration research of traditional clothing and the measurement of cultural relics.

Key words: dimensional measurement, key dimensions of costume, Han-style costume, convolutional neural network, transfer learning

CLC Number: 

  • TS941.79

Fig.1

GlobalNet pyramid network structure"

Fig.2

Two-stage convolutional neural network structure diagram"

Fig.3

Flow chart of migration training"

Tab.1

Key point detection results after first training"

类型 测量
对象
张数		 含不同个数关键点图片张数 单点
准确
率/%		 漏识
别率/
%		 识别
准确
率/%
13
个		 10~13
个		 10~7
个		 7个
以下
现代汉服 50 20 15 15 0 68 0 40
古代汉服 50 17 14 19 0 61 0 34

Tab.2

Key point detection results after second training"

类型 测量
对象
张数		 含不同个数关键点图片张数 单点
准确
率/%		 漏识
别率/
%		 识别
准确
率/%
13个 10~13
个		 7~10
个		 7个
以下
现代汉服 50 44 6 0 0 95 0 92
古代汉服 50 40 8 2 0 86 0 80

Fig.4

Detection effect of Han-style costumes after first training. (a) Modern Han-style costumes ; (b) Ancient Han-style costumes"

Fig.5

Detection effect of Han-style costumes after second training. (a) Modern Han-style costumes; (b) Ancient Han-style costumes"

Tab.3

Size measurement table of women's jacket with geometric patterns"

上衣
部位		 实际值/
mm		 像素距
离/像素		 测量
值/mm		 绝对误
差/mm		 相对误
差/%
领口宽 160 79 165 5 3.13
袖口宽 120 55 115 5 4.17
摆宽 1 120 530 1 108 9 0.80
衣长 725 344 719 6 0.83

Tab.4

Size measurement table of plain silk shirt"

上衣
部位		 实际值/
mm		 像素距
离/像素		 测量值/
mm		 绝对误
差/mm		 相对误
差/%
领口宽 100 55 97 3 3.00
袖宽 680 384 676 4 0.59
衣长 810 456 803 7 0.86

Tab.5

Size measurement table of blue crepe short women's Bufu with unicorn pattern"

上衣
部位		 实际值/
mm		 像素距
离/像素		 测量值/
mm		 绝对误
差/mm		 相对误
差/%
袖宽 360 203 366 6 1.67
腰宽 590 331 597 7 1.19
衣长 630 344 621 9 1.43
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