The 3D Chinese head and face modeling

• Published in: Computer aided design Vol. 44; no. 1; pp. 40 - 47
• Main Authors: Luximon, Yan, Ball, Roger, Justice, Lorraine
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 2012
• Subjects: 3D modeling; Algorithms; Clouds; Design; Design engineering; Ergonomics; Fittings; Head and face; Human body; Mathematical models; Principal component analysis; Product design; Three dimensional; Design; 3D modeling; Head and face; Ergonomics; Principal component analysis
• ISSN: 0010-4485; 1879-2685
• DOI: 10.1016/j.cad.2011.01.011

Perfect fit for people has always been a target for product design. Designers commonly use traditional anthropometric dimensions for 3D product design thus creating a lot of fitting problems when dealing with the complexities of human body shapes. The development of recent 3D anthropometric survey has created an opportunity for complex shape analysis on human model by collecting 3D scan data. Using 3D point cloud data from the SizeChina survey, a methodology of creating a homologous 3D head and face model was demonstrated in this study. Anatomical and virtual landmarks, and surface modeling algorithm based on point cloud data were applied in building the model. The head and face models for all scans had the same amount of vertices with consistent features. The average Chinese models showed obvious differences between male and female. The variations of head and face shapes were analyzed using Principal Component Analysis and the results showed that the largest variations among people were general size, especially for width and depth. However face height, forehead, back of the head, chin and jaw area were also important when describing the 3D shape. The results from this study may be useful in the design of head and facial products. ► Using 3D point cloud data from the SizeChina survey, a methodology of creating a homologous 3D head and face model was demonstrated in this study. ► Anatomical and virtual landmarks, and surface modeling algorithm based on point cloud data were applied in building the model. ► The variations of head and face shapes were analyzed using Principal Component Analysis and the results showed that the largest variations among people were general size, especially for width and depth.