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Research Papers

Automatically Creating Design Models From 3D Anthropometry Data

[+] Author and Article Information
Stefanie Wuhrer

Saarland University,
Department of Cluster of Excellence MMCI,
Saarbrücken, 66123 Germany
e-mail: swuhrer@mmci.uni-saarland.de

Chang Shu

National Research Council of Canada,
Ottawa, K1A Canada
e-mail: chang.shu@nrc-cnrc.gc.ca

Prosenjit Bose

Carleton University,
Department of School of Computer Science
Ontario, Ottawa, K1S 5B6 Canada
e-mail: jit@scs.carleton.ca

Contributed by the Design Engineering Division of ASME for publication in the Journal of Computing and Information Science in Engineering. Manuscript received January 16, 2012; final manuscript received August 2, 2012; published online November 15, 2012. Assoc. Editor: Xiaoping Qian.

J. Comput. Inf. Sci. Eng 12(4), 041007 (Nov 15, 2012) (7 pages) doi:10.1115/1.4007839 History: Received January 16, 2012; Revised August 02, 2012

When designing a product that needs to fit the human shape, designers often use a small set of 3D models, called design models, either in physical or digital form, as representative shapes to cover the shape variabilities of the population for which the products are designed. Until recently, the process of creating these models has been an art involving manual interaction and empirical guesswork. The availability of the 3D anthropometric databases provides an opportunity to create design models optimally. In this paper, we propose a novel way to use 3D anthropometric databases to generate design models that represent a given population for design applications such as the sizing of garments and gear. We generate the representative shapes by solving a covering problem in a parameter space. Well-known techniques in computational geometry are used to solve this problem. We demonstrate the method using examples in designing glasses and helmets.

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Figures

Grahic Jump Location
Fig. 4

Greedy covering of parameter space. Left: Complete covering. Right: Covering with three boxes. Unit along axes is meters. Points P are shown as black points, boxes Bi are shown as red boxes, and the design model for each box is shown.

Grahic Jump Location
Fig. 5

Measurements used to define parameter space

Grahic Jump Location
Fig. 1

Faces obtained using feature analysis

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Fig. 2

Measurements used to define parameter space

Grahic Jump Location
Fig. 3

Covering parameter space with ɛ=1.25. Unit along axes is meters. Points P are shown as black points, boxes Bi are shown as red boxes, and the design model for each box is shown.

Grahic Jump Location
Fig. 6

Left: Greedy complete covering of parameter space. Right: Greedy covering of parameter space with three boxes. Points P are shown as black dots, centers of boxes Bi are shown as red dots, and the design model for each box is shown.

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