Revealing the internal structure of human variability for design purposes
The strength of traditional anthropometric data stems from its simplicity, ease of use, and ease of understanding. Designers are familiar with it and have been using it in a multitude of applications, albeit with varying degrees of success. But perhaps chief among weaknesses is the fact that traditional data does not capture shape, which was difficult to acquire many years ago, adequately. Now that shape information is easily captured by 3D scanning systems, along with the richness of information has appeared the burden of extracting the useful attributes of the data for individuals and an even greater burden when it comes to characterizing populations. This significant stumbling block has stood in the way of widespread use of 3D human shapes and its effective application in design projects. Recent developments in statistical shape analysis have removed the tedium of cleaning the scans and have opened the door to the use of statistical representations of human shape. One technique, principal components analysis (PCA), has proven particularly helpful in representing population variability and given designers enough insight into the modes of variability to allow them to address it in the early stages of design.The purpose of this paper is to explain some of the options currently available for 3D design and present a new tool that provides a new paradigm for addressing population accommodation. The pros and cons of the new tool will be discussed in the context of an application for a new military helmet design, and conclusions, recommendations and challenges for the future will be proposed. The paper will hopefully show a need to rethink how to account for and deal with population shape variability.
Pierre Meunier Chang Shu Pengcheng Xi
Defence R&D Canada National Research Council of Canada
国际会议
17th World Congress on Ergonomics(第十七届国际人类工效学大会)
北京
英文
1-5
2009-08-09（万方平台首次上网日期，不代表论文的发表时间）