Garment patterns generating based on 3-D body scanning

Abstract

准确与合体的服装版型对于服装生产来说至关重要。尽管三维人体扫描仪可获得人体数据,但从以往文献来看,从三维人体数据生成二维服装版型仍存在挑战。本文的目的是将三维人体点云数据经过一系列步骤,自动生成服装基础版型。这些步骤包括:从三维扫描得到人体数据,将这些散乱数据进行人体识别,将识别后的模型Delaunay三角化,对三角化后的人体模型进行C均值模糊聚类的人体曲面分割,基于最小二乘法的多边形近似及展开,最后自动生成服装样版。 It is important to make accurate garment patterns for fitting wearers in the garment manufacturing industry.Though virtual 3-D body scanning technology can now obtain body data,previous documents show that it is a challenging work to transform 3-D body data into a 2-D pattern.This paper presents a new method for generating 2-D garment patterns directly from 3-D human body point cloud.The new method consists of five steps,namely body recognition,body modeling,body surface clustering,planar fitting and planar co-planarization.In the paper,algorithms for body feature extraction and body modeling are firstly described,the relationship between human body,patterns and darts are then investigated,and pattern construction through automatic dart transformation are finally developed.This paper has demonstrated how the proposed method can generate 2-D garment patterns from 3-D instructed point clouds.