A general framework to generate sizing systems from 3D motion data applied to face mask design
For the design of mass-produced wearable objects for a population it is important to find a small number of sizes, called a sizing system, that will fit well on a wide range of individuals in the population. To obtain a sizing system that incorporates the shape of an identity along with its motion, we introduce a general framework to generate a sizing system for dynamic 3D motion data. Based on a registered 3D motion database a sizing system is computed for taskspecific anthropometric measurements and tolerances, specified by designers. We generate the sizing system by transforming the problem into a box stabbing problem, which aims to find the lowest number of points stabbing a set of boxes. We use a standard computational geometry technique to solve this; it recursively computes the stabbing of lower-dimensional boxes. We apply our framework to a database of facial motion data for anthropometric measurements related to the design of face masks. We show the generalization capabilities of this sizing system on unseen data, and compute, for each size, a representative 3D shape that can be used by designers to produce a prototype model.
|Keywords||3D face modeling, Design models, Face mask design|
|Conference||2014 2nd International Conference on 3D Vision, 3DV 2014|
Bolkart, T. (Timo), Bose, P, Shu, C. (Chang), & Wuhrer, S. (Stefanie). (2015). A general framework to generate sizing systems from 3D motion data applied to face mask design. Presented at the 2014 2nd International Conference on 3D Vision, 3DV 2014. doi:10.1109/3DV.2014.43