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Measuring to Fit: Virtual Tailoring Through Cluster Analysis and Classification

  • Herna L. Viktor
  • Eric Paquet
  • Hongyu Guo
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4213)

Abstract

Clothes 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.

Keywords

Body Measurement Neck Circumference Target Concept Body Scan Typical Consumer 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Herna L. Viktor
    • 1
  • Eric Paquet
    • 2
  • Hongyu Guo
    • 1
  1. 1.School of IT and EngineeringUniversity of OttawaOttawaCanada
  2. 2.Visual Information Technology GroupNational Research Council of CanadaOttawaCanada

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