• DocumentCode
    2639047
  • Title

    3D Fashion Fast Modeling from Photographs

  • Author

    Li, Wei-Long ; Lu, Guo-Dong ; Geng, Yu-Lei ; Wang, Jin

  • Author_Institution
    State Key Lab. of CAD&CG, Zhejiang Univ., Hangzhou, China
  • Volume
    1
  • fYear
    2009
  • fDate
    March 31 2009-April 2 2009
  • Firstpage
    738
  • Lastpage
    742
  • Abstract
    The paper presents a technique of 3D fashion modeling from photographs of wearing clothes in front and back views. Firstly, an efficient segmentation method is applied on photographs to obtain the silhouette of the fashion. Then, a template-based feature extraction algorithm is introduced to determine the feature points on the garment. Finally, a view-dependent deformation technique is described to construct the fashion by deforming the garment template. Our segmentation algorithm is derived from mathematical morphology and image difference method. The deformation technique is related to free-form deformations and vector field of mannequin. With our deformation method, the main feature of fashion is preserved. Compared with other predefined fashion modeling approaches, the efficient and realistic of constructing is greatly increased. The functionality of garment model constructed by our method can apply to some others applications for garment industry.
  • Keywords
    clothing industry; feature extraction; image segmentation; image texture; mathematical morphology; photography; production engineering computing; 3D fashion fast modeling; garment industry; image difference method; mathematical morphology; photograph; segmentation method; template-based feature extraction algorithm; view-dependent deformation technique; Biological system modeling; Clothing; Computer science; Deformable models; Feature extraction; Flowcharts; Humans; Image segmentation; Morphology; Paper technology;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Science and Information Engineering, 2009 WRI World Congress on
  • Conference_Location
    Los Angeles, CA
  • Print_ISBN
    978-0-7695-3507-4
  • Type

    conf

  • DOI
    10.1109/CSIE.2009.838
  • Filename
    5171272