Measuring to Fit: Virtual Tailoring through Cluster Analysis and Classification

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TypeArticle
ConferenceThe 17th International European Conference on Machine Learning and the 10th European Conference on Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD 2006), September 18-22, 2006., Berlin, Germany
AbstractClothes should be designed to tailor well, fit the body elegantly and hide obvious body flaws. To attain this goal, it is crucial to know the interrelationships between different body measurements, such as the interplay between e.g. shoulder width, neck circumference and waist. This paper discusses a study to better understand the typical consumer, from a virtual tailor's perspective. Cluster analysis was used to group the population into five clothing sizes. Next, multi-relational classification was applied to analyze the interplay between each group's anthropometric body measurements. Throughout this study, three-dimensional (3-D) body scans were used to verify the validity of our findings. Our results indicate that different sets of body measurements are used to characterize each clothing size. This information, together with the demographic profiles of the typical consumer, provides us with new insight into our evolving population.
Publication date
LanguageEnglish
AffiliationNRC Institute for Information Technology; National Research Council Canada
Peer reviewedNo
NRC number48749
NPARC number5764813
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Record identifier24ec87c1-576b-4774-a926-b59c7188c80c
Record created2009-03-29
Record modified2016-05-09
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