Automatic Block Pattern Generation from a 3D Unstructured Point Cloud

Haiqiao Huang, P. Y. Mok, Y. L. Kwok, J. S. Au

Research output: Journal article publicationJournal articleAcademic researchpeer-review

4 Citations (Scopus)


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 isconstrained 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 relationshipbetween 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.

Original languageEnglish
Pages (from-to)26-37
Number of pages12
JournalResearch Journal of Textile and Apparel
Issue number1
Publication statusPublished - 1 Feb 2010


  • Block Pattern Generation
  • Body Segmentation
  • Clothing
  • Clustering Body Surface
  • Garment Patterns

ASJC Scopus subject areas

  • Materials Science (miscellaneous)
  • Industrial and Manufacturing Engineering
  • Business and International Management
  • Management of Technology and Innovation


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