A graph modeling and matching method for sketch-based garment panel design

Shuang Liang, Rong Hua Li, George Baciu

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

6 Citations (Scopus)

Abstract

In the past decade, fashion industry and apparel manufacturing have been applying intelligent CAD technologies to operate garment panel shapes in digital form. As garment panels are being accumulated gradually, there is a growing interest in finding similar panel shapes from large collections. The retrieved panel shapes can provide recommendations for stylists to reference and re-create during the cognitive fashion design process. In this paper, we propose a novel graph modeling and matching method to facilitate the searching of panel shapes for sketch-based garment design. A panel shape is first decomposed into a sequence of connected segments and represented by the proposed bi-segment graph (BSG) model to encode its intrinsic features. A new matching metric based on weighted direct product graph and minimal spanning tree (WDPG-MST) is then proposed to compute the similarity between two BSG models of the panel shapes. Finally in the front-tier, we provide a sketching interface based on our previous work for designers to input and edit the clothing panels. 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
Title of host publicationProceedings of the 10th IEEE International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2011
Pages340-347
Number of pages8
DOIs
Publication statusPublished - 3 Oct 2011
Event10th IEEE International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2011 - Banff, AB, Canada
Duration: 18 Aug 201120 Aug 2011

Conference

Conference10th IEEE International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2011
Country/TerritoryCanada
CityBanff, AB
Period18/08/1120/08/11

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Cognitive Neuroscience

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