High Technology in the Apparel Industry: In a Matter of Minutes, Eight Cameras Coupled with Computer Software Can Generate Three-Dimensional Images of the Human Form, Both Clothed and Unclothed. Researchers in Cornell's Department of Textiles and Apparel Know That This Technology Has the Power to Revolutionize Ready-to-Wear Fashion. They Are Collaborating with Industry to Prove It

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The lead patternmakers for manufacturing services with Liz Claiborne's Casual Division are impressed by the technology. They have spent their careers designing patterns for mass-produced clothing, but they had only seen how clothing fit on one very special woman, the original model for their pattern forms, until Suzanne Loker brought them new data.

"The patternmakers are fascinated to see how their patterns fit on the real people who buy them today," says Loker, a professor of textiles and apparel and J. T. Clark Professor of Entrepreneurship. She is providing Liz Claiborne patternmakers with data from the scanned body images of 200 women, who were chosen to be scanned because they have the same demographics as Liz Claiborne customers. The patternmakers have been able to view three-dimensional visualizations of these women virtually wearing their pants. "Patternmakers typically only see how their patterns look on a single fit model for each division," Loker explains, "not on bodies of all the shapes and sizes of their customers."

Body-scanning technology is capable of changing that. When scanned images of a person in a bodysuit and the same person in clothing are electronically layered or merged, the composite can be measured to capture exactly how the clothing fits on the individual person. It is also possible to see exactly how the garment fits in three dimensions.

Loker and co-investigator Susan Ashdown, associate professor of textiles and apparel, are using a body scan to design better-fitting garments fora company's target market--in Liz Claiborne's case, this market is 34- to 54-year-old women of a defined household income who are likely to work outside the home. Because their research focuses on measurements of members of this target market, they believe it will make the most immediate impact on improving fit for consumers--and on decreasing return rates based on poor fit. But this was not how early proponents of body-scan technology imagined it would be used. It originally was thought that the scans would be used to create either customized patterns or customized garments, made to order.

"From the beginning, we questioned how much customized clothing would really be ordered by consumers," says Loker, who has worked closely with the apparel industry for more than 22 years. "What we knew for sure is that the apparel industry makes a great deal of ready-to-wear clothing, yet so little of it fits."

In their study, Loker and Ashdown are collaborating with Carol Adelson, a specialist in patternmaking at the Fashion Institute of Technology in New York City. Adelson is helping to identify which of the 300,000 data points on each body scan matter the most in terms of the way a pattern is constructed and fits.

Loker and Ashdown also asked the 34- to 55-year-old female participants in their study what kinds of commercial applications of the body scanner most appealed to them. The response was clear. What these first test subjects most wanted was what is called the "virtual try-on."

During a virtual try-on, a scan of a person's body is uploaded onto a computer. Then images of garments are superimposed on the person's form--a process much like clothing three-dimensional paper dolls, and these images can rotate to provide a back view. The consumer can see which styles and sizes best fit and are most flattering. An added benefit is that this virtual try-on can take place while the consumer sits in a comfortable arm-chair--no need for fitting rooms.

Another body-scanning application that the consumers in the study liked is called size prediction. A person's body scan is entered into a database containing a variety of styles and sizes of garments made by, for example, 20 different apparel manufacturers. The computer assesses the fit of each on the consumer's body-scan image. Without having to go from store to store to try on the actual items, a person could learn that a certain company's blouse would fit best, whereas they would be fitted better in another's trousers and a third's bathing suit. …