TY - JOUR
T1 - Three Dimensional Pattern Grading Based on Deformable Body Features and 3D Developable Surface
AU - Yingnan Wang & Haiqiao Huang
JO - Journal of Fiber Bioengineering and Informatics
VL - 2
SP - 115
EP - 128
PY - 2011
DA - 2011/04
SN - 4
DO - http://doi.org/10.3993/jfbi06201102
UR - https://global-sci.org/intro/article_detail/jfbi/4908.html
KW - 3D Pattern Grading
KW - Garment Grading
KW - Developable Garment
KW - Ease Distribution
KW - Sizing Chart
AB - The garment pattern grading is a crucial procedure for manufacturing full sizes of clothing products. This
procedure traditionally starts with an ‘average’ pattern and generates a set of sized garment patterns by
extending the ‘average’ pattern. The quality of the graded patterns depends on the grading technique and
the technician's experience. However, the garment patterns are often graded based on two-dimensional
rules that hardly provide an accurate fit because of shape variations and complexity of 3D human bodies.
Additionally, the traditional pattern grading is conducted manually and very time-consuming. In this
paper, we propose a new automatic approach of generating full sizes of garment patterns by flattening
3D garments created from parameterized mannequins in fulfilling the requirements of body structures,
sizing chart and garment fit. Firstly, a parametric human body model is introduced called Horizontal
Piecewise B-spline Curves (HPBC) model. Three types of novel frames are developed from the HPBC
model, namely feature frame, size frames, and ease frames. Based on these frames, a range of fit and
flattenable 3D garments are established. Finally, the graded patterns can be generated by flattening
these 3D garments.