Abstract
Within the framework of recent advances in Three-Dimensional Virtual Prototyping (3DVP) in the clothing industry, a methodology for unsupervised classification of human bodies is developed. The aim is to identify virtual mannequins representative of subsets of a population, from given sets of Three-Dimensional (3D) scan data, accompanied by derived sets of body measurements. Applying interpolation techniques, humanoids ready to be virtually dressed and animated, can then be derived for each representative body. The classification tool will be integrated into a platform for e-collaboration, enabling designers and other actors to visualise new creations on virtual mannequins representative of the body shape variations inherent in an anthropometric database. Although the selected human body shape representation was as minimal as possible, through the application of multivariate analysis, the clustering results reflect meaningful body shape variations.
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