Cognitive garment panel design based on BSG representation and matching

S. Liang, George Baciu, George Baciu

Research output: Journal article publicationJournal articleAcademic researchpeer-review


Previously, the fashion industry and apparel manufacturing have been applying intelligent CAD technologies with sketching interfaces to operate garment panel shapes in digital form. The authors propose a novel bi-segment graph (BSG) representation and matching approach to facilitate the searching of panel shapes for sketch-based cognitive garment design and recommendation. First in the front-tier, they provide a sketching interface for designers to input and edit the clothing panels. A panel shape is then decomposed into a sequence of connected segments and represented by the proposed BSG model to encode its intrinsic features. A new matching metric based on minimal spanning tree is also proposed to compute the similarity between two BSG models. The simulation of the resulting garment design is also visualized and returned to the user in 3D. Experiment results show the effectiveness and efficiency of the proposed method.
Original languageEnglish
Pages (from-to)84-99
Number of pages16
JournalInternational journal of software science and computational intelligence
Issue number1
Publication statusPublished - 2012


  • Bi-Segment graph
  • Computer aided design
  • Fashion industry
  • Garment panel design
  • Sketching interface


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