Parametric modeling of 3D human faces using anthropometric data

Personalized design is a current trend in the field of consumer products. It aims to enhance the value added by a product or service by satisfying individual customer requirements. This research proposes a design method for mass personalization of eyeglass frames. Three-dimensional (3D) face models of Taiwanese females aged 18 to 25 were constructed using non-contact scanning technologies. Principal Component Analysis (PCA) was applied to reduce data complexity while preserving sufficient data variance. Parametric models based on linear regression and Kriging were developed to correlate the mesh point coordinates of a face model to a set of feature parameters. These models efficiently generate 3D facial geometry approximating to individual users. A design software tool implementing Free Form Deformation (FFD) was introduced to adjust the frame design interactively and to enable real-time design evaluation. This study enhances the practical value of 3D anthropometric data by realizing the concept of human-centric design.