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Cosmetic mask is a popular skincare product widely accepted by the youth and female. Most cosmetic masks in the current market offer very few sizes to choose from, thus producing misfit masks with reduced wearing comfort and skincare functionality. This paper describes how to realize customized design of cosmetic masks using three-dimensional (3D) parametric face models derived from a large amount of scanned facial data. The parametric models approximate individual faces using a nonlinear regression model controlled by a set of facial parameters easy to be measured. They serve as effective reference geometry to conduct 3D mask design. A prototyping mask design system implementing the parametric modeling method demonstrates the customized design process. The system allows the user to construct the mask shape directly on 3D meshes of a face model by specifying inner and outer boundary curves. An automatic flattening function unfolds the trimmed meshes into a two-dimensional (2D) pattern with a reduced shape distortion. This research enhances the practical value of large-scale anthropometric data by realizing human centric design customization using cosmetic facial mask as an example.

Personalized design enhances the values added by a product or service by satisfying individual customer requirements. It has become a trend in consumer product development nowadays. This paper proposes a method for design personalization of the eyeglasses frame using anthropometric data. Three-dimensional face models were constructed using non-contact scanning devices. Principal Component Analysis (PCA) was applied to reduce the data complexity while preserving sufficient data variance. Kriging based parametric models correlate the mesh point coordinates of a face model to a set of feature parameters. The correlation allows synthesizing and controlling 3D facial geometry approximating to individual users with given parameter values. Rendering the synthesized geometry with human face images generates realistic face models. These models not only allow adjusting the frame design in real-time, but also evaluating whether or how the design style fits individual face characteristics. This study enhances the practical values of 3D anthropometric data by realizing the concept of human-centric design.

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 humancentric design.

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