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...

Full description

Saved in:
Bibliographic Details
Main Authors: Chun-Yang Tseng, I-Jan Wang, Chih-Hsing Chu
Format: Conference Proceeding
Language:English
Subjects:
anthropometric data
Data models
face models
Linear regression
Parametric modeling
Parametric statistics
personalized design
Principal component analysis
Shape
Solid modeling
Three-dimensional displays
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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.
ISSN:2157-3611
2157-362X
DOI:10.1109/IEEM.2014.7058686