Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/67292
Title: Automatic block pattern generation from a 3D unstructured point cloud
Authors: Huang, HQ
Mok, PY 
Kwok, YL
Au, SC 
Keywords: Clothing
Block pattern generation
Body segmentation
Clustering body surface
Garment patterns
Issue Date: 2010
Publisher: Emerald Group Publishing Limited
Source: Research journal of textile and apparel, 2010, v. 14, no. 1, p. 26-37 How to cite?
Journal: Research journal of textile and apparel 
Abstract: Accurate and fitted garment patterns are fundamentally important in garment manufacturing. Even though a virtual body can now be obtained by 3D scanning, the problem of generating patterns model is still challenging because the mapping from a 3D body to 2D pattern is constrained by complex garment style information and sewing definitions. This paper presents a new approach for generating 2D block patterns directly from scanned 3D unstructured points of the human body. The new approach consists of a series of steps from body recognition, body modelling to pattern formation. In the paper, algorithms for body feature extraction and body modelling are first described, then the relationship between the human body, patterns and darts are investigated, and pattern creation through automatic dart transformation are thus developed. The paper has demonstrated that the proposed method can generate 2D block patterns from a 3D unstructured point cloud.
URI: http://hdl.handle.net/10397/67292
ISSN: 1560-6074
DOI: 10.1108/RJTA-14-01-2010-B003
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