Feature-Based Human Model for Digital Apparel Design

Shuxia Wang, Shengfeng Qin, Congying Guan

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)


Three-dimensional (3D) body scanning technology opens opportunities for virtual try-on and automatic made-to-measure apparel design. This paper proposes a new feature-based parametric method for modeling human body shape from scanned point clouds of a 3D body scanner $[{rm TC}]^{2}$. The human body model consists of two layers: the skeleton and the cross sections of each body part. First, a simple skeleton model from the body scanner $[{rm TC}]^{2}$ system has been improved by adding and adjusting the position of joints in order to better address some fit issues related to body shape changes such as spinal bending. Second, an automatic approach to extracting semantic features for cross sections has been developed based on the body hierarchy. For each cross section, it is described by a set of key points which can be fit with a closed cardinal spline. According to the point distribution in point clouds, an extraction method of key points on cross sections has been studied and developed. Third, this paper presents an interpolation approach to fitting the key points on a cross section to a cardinal spline, in which different tension parameters are tested and optimized to represent simple deformations of body shape. Finally, a connection approach of body parts is proposed by sharing a boundary curve. The proposed method has been tested with the developed virtual human model (VHM) system which is robust and easier to use. The model can also be imported in a CAD environment for other applications.
Original languageEnglish
Pages (from-to)1-7
JournalIEEE Transactions on Automation Science and Engineering
Publication statusPublished - 28 Jan 2014
Externally publishedYes


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