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Improvement of Cross Sectional Distance Measurement Method of 3D Human Body

3차원 인체 형상의 공극거리 측정 방법 효율성 향상을 위한 연구

  • Kim, Min-Kyoung (Dept. of Clothing and Textiles, Seoul National University) ;
  • Nam, Yun-Ja (Dept. of Clothing and Textiles, Seoul National University/Research Institute of Human Ecology, Seoul National University) ;
  • Han, Hyun-Sook (Dept. of Clothing and Textiles, Seoul National University) ;
  • Choi, Young-Lim (Research Institute of Human Ecology, Seoul National University)
  • 김민경 (서울대학교 의류학과) ;
  • 남윤자 (서울대학교 의류학과/서울대학교 생활과학연구소) ;
  • 한현숙 (서울대학교 의류학과) ;
  • 최영림 (서울대학교 생활과학연구소)
  • Received : 2011.08.23
  • Accepted : 2011.10.20
  • Published : 2011.12.31

Abstract

This study is designed to develop programs that analyze the distance of clothes from human skin and cross-sectional body figures based on 3D human body scan data, and to verify accuracy and efficiency of the program so that it can be used for clothing fit evaluation and 3D human body research. The auto cross-sectional imaging program was developed by using Visual C++ and OpenGL, and the 3D human body scan data were adopted to measure the space between skin and clothing. The space measurements were obtained by two widely used programs, RapidForm and AutoCAD, and a program devised by the researchers of this study. Measuring time and space measurements from different programs were compared in order to verify accuracy and efficiency of the newly-devised program. As a result, no significant difference was found in the measurements. However, the required time to measure one cross section was different within the significance level of 0.05, and the differences become more remarkable as the number of measuring and the angle of space between skin and clothing increase. Therefore, the program developed by this study is expected to be useful for research on body shapes and fit evaluation based on 3D human body scan data in the fashion field.

Acknowledgement

Supported by : 정보통신산업진흥원

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  2. Analysis of cross sections and silhouette in body shape according to girdle worn using 3D body scanner vol.23, pp.2, 2015, https://doi.org/10.7741/rjcc.2015.23.2.242