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Home > Archive>Volume 27, Issue 10, 2016 >2574-2586. DOI:10.13328/j.cnki.jos.005071
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Data-Driven Method for Rapid 3D Garment Modeling
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National Natural Science Foundation of China (61462051, 61272192, 61379112, 61462056); Applied Fundamental Research Project of Yunnan Province (2014FB133); Applied Fundamental Research Key Project of Yunnan Province (2014FA028); Nature Science Foundation of Kunming University of Science and Technology (201403119)

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    Abstract:

    This paper presents a data-driven method for rapid 3D garment modeling, which can efficiently generate new garments by examples. First, a semantic segmentation is applied to simultaneously segment and label the components in given 3D garments using shape analysis of garment styles. Second, the garment components are clustered into a garment component library with four categories including tops, bottoms, sleeves, and accessories. Third, a continuous style description of the 3D garments, characterized by the ratio of area and boundary length, is constructed to recommend components that can be regarded as a new 3D garment. The final new suitable garments are produced by optimizing two component meshes. Experimental results show that the presented method is able to satisfy the new requirements of online 3D model collections while ensuring the efficiency of 3D garment modeling.

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刘骊,王若梅,罗笑南,付晓东,刘利军.数据驱动的三维服装快速建模.软件学报,2016,27(10):2574-2586

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History
  • Received:January 04,2016
  • Revised:March 29,2016
  • Online: August 11,2016
Links:Institute of Software, CASChina Computer FederationCASNSFC
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