When designing a product that needs to fit the human shape, designers often use a small set of 3D models, called design models, either in physical or digital form, as representative shapes to cover the shape variabilities of the population for which the products are designed. Until recently, the process of creating these models has been an art involving manual interaction and empirical guesswork. The availability of the 3D anthropometric databases provides an opportunity to create design models optimally. In this paper, we propose a novel way to use 3D anthropometric databases to generate design models that represent a given population for design applications such as the sizing of garments and gear. We generate the representative shapes by solving a covering problem in a parameter space. Well-known techniques in computational geometry are used to solve this problem. We demonstrate the method using examples in designing glasses and helmets.
A method of calculating representative forms from a given set of forms was developed, in which surface data is modeled by polygons based on landmarks. Inter-individual distances are defined as distortions in FFD control points. By calculating inter-individual distances for all possible pairs of forms, the distribution of the 3D forms in m-dimensional space is obtained using MDS. Each MDS dimension represents an independent shape factor. Forms with specific MDS scores, such as (0.5,0,0,0), (1,0,0,0) in standard deviation units, are calculated as weighted averages of all actual forms. An FFD transformation grid is calculated that represents the systematic form transformation along an MDS dimension. Forms with different scores for the first or second MDS dimensions only and average scores (=0) for the other MDS dimensions are calculated using these transformation grids.