Purpose
– The purpose of this paper is to focus on the determination of distance ease of pants from the 3D scanning data of a clothed and unclothed body.
Design/methodology/approach
– A human model whose body size conformed to the Chinese dummy standard and four pairs of suit pants were chosen for the study. The scanned surfaces of both the body and the pant were superimposed based on the preset markers. The circumferences at four important positions – abdomen, hip, thigh and knee – were selected for pant ease determination. At one position (e.g. hip), the two cross-sections were divided into several characteristic sections and the distance ease, i.e. the space between the cross-sections at each section was measured. The regression equations between the distance ease and ease allowance were then derived so that the distance ease can be estimated.
Findings
– The relationship was found between the distance ease and the ease allowance. Meanwhile, a mathematic model was established to convert the distance ease into the increments of a pant pattern, which helps to develop an individual pant pattern automatically.
Social implications
– The paper provided the concept and the method to customize a pant by using the 3D scanning data of body. It created a link between the 3D distance ease and the 2D ease allowance, and the model to calculate the distance ease increments which warrant proper ease distributions. The method helps to develop an individualized garment pattern automatically from a basic and tight pant pattern.
Originality/value
– Understanding the relationship between the distance ease and the ease allowance and increments of pattern could help develop an individual apparel pattern from 3D measurements. This paper showed a way to solve the problem of distribution of the apparel ease in a virtual environment and convert body measurements from a 3D scanner into personalized apparel patterns.
Shape distortion analysis of drawing die by optical 3D scanning