Home > Uncategorized > Cornell University Body Scanning

Cornell University Body Scanning

download.jpg

 

 

BODY SCAN TECHNOLOGY will help apparel firms improve the fit of their mass-produced clothing by providing valuable measurement data on consumer populations. Most systems for sizing ready-to-wear garments have been based on very limited information. Before scan studies were possible, the last traditional anthropometric (body-measurement) survey of the civilian population for apparel sizing purposes was conducted in 1941 and was not accurate for modern body shapes.


Population Studies


BODY SCAN TECHNOLOGY will help apparel firms improve the fit of their mass-produced clothing by providing valuable measurement data on consumer populations. Most systems for sizing ready-to-wear garments have been based on very limited information. Before new body scanner technology made anthropometric (body-measurement) studies affordable, many sizing systems were based on a traditional survey of the civilian population conducted in 1941 that is not accurate for today’s body shapes.

In the past, apparel firms have not had anthropometric data, and therefore based many decisions about sizing on experimentation and subsequent feedback from their customers. This is not a very effective system for gathering data, as most consumers make decisions about garment fit at home or in the fitting room and do not communicate their experiences reliably or at all.

Few traditional anthropometric surveys were conducted because of the high labor costs associated with measuring large numbers of people with traditional tools. Body scanners have changed this. Apparel companies will benefit from several anthropometric studies that have scanned or are currently scanning representative groups of people from the population. The goal of these studies is to gain a better understanding of the current human sizes and shapes in order to develop sizing systems that fit most of the population.

Body scans illustrate significant variation in proportions among three women, each of whom wears a size 10 pant. (Image: Cornell Body Scan Research Group)

The CAESAR study, an international anthropometric study conducted in the United States, the Netherlands, and Italy, was funded by the automotive, airline, and apparel industries and its data is being used in the design of many products. The Textile and Clothing Technology Corporation, [TC]2, organized a consortium of university and industry partners to collect 12,000 scans of men and women in 50 locations in the United States to create a database of civilian anthropometric data for the apparel industry. The data from this study, called SizeUSA, is widely used by apparel companies to help improve their sizing systems.

The last traditional anthropometric survey of the civilian population for apparel sizing purposes was conducted in 1941. (Image: Cornell Body Scan Research Group )


Sizing Systems


A sizing system is a set of clothing sizes that is created by an apparel firm to fit the range of people in a target market. The most common type of sizing system in the apparel industry starts with a base size which is then proportionally graded (scaled) to create a multiple set of sizes. Sizing systems can use generic labels, such as small, medium, large, and extra large; numbered sizes such as 10, 12, and 14; or body measurements such as 17″ neck and 32″ sleeve length. Sizing systems vary in range from only a few sizes to a full spectrum of sizes 2-20.

Typically, an apparel company arrives at a sizing system for a product line as follows. First, it defines a target market and typical customers by identifying demographic characteristics, such as age, income, ethnicity, and lifestyle. Then the firm chooses a single person — the “fit model” — to be the idealized body shape for that product and market. Prototype garments are created, then evaluated and modified in fitting sessions on the single fit model. A base size pattern, often size 8 for women, is perfected for this prototype garment, and proportional grade rules are used to scale a set of patterns up and down for the rest of the size range, e.g., 2-16.

Proportional grade rules do not address the differences in the basic shapes and body proportions of the population, such as small or large waist, short or long torso, or the differences across ages and target markets. A single fit model has a particular body shape that is translated to the full range of sizes. Providing good fit using a finite set of sizes for an almost infinite range of body types is a challenging task. The new information available from the 3D body scan research will help us meet this challenge.

The star on this graph identifies the fit model, whose measurements are used to develop a sizing system for a company’s target market. The other points on the graph display the pant fit for 140 female subjects with various body proportions. Since the pants for each subject were chosen by hip fit, the hip trend line (blue) is flattest, indicating the least variation in fit at the hip. The waist trend line (red) indicates the greatest variation in pant fit: people who have straighter proportions than the fit model will have tight pants at the waist. Those with curvy proportions are closer to the fit model’s measurements and are better fitted. (Image: Cornell Body Scan Research Group)
In standard grading, each pattern is scaled proportionally to the others, as seen in this stacked set of patterns. These proportions cannot reflect all of the body shapes in the population. (Image: Cornell Body Scan Research Group)
This sample grade rule table dictates adjustments at different locations on a pattern (indicated by the blue numbers) for the range of clothing sizes. (Image: Cornell Body Scan Research Group)


Our Initial Research Program


Research conducted by Cornell professors Susan Ashdown and Suzanne Loker (see Contributors) challenges some of the assumptions behind methods now used by apparel companies to develop sizing systems. Research projects explore the role body scan data can play in satisfying consumers’ desire for good fit while advancing the competitiveness of the domestic apparel industry. The focus of the research is to find ways to use body scanners to improve current practices. The initial research project at Cornell was funded by the National Textile Center and focused on improving ready-to-wear sizing systems.

Initial research focused on the development of protocols for collecting body scan data — including issues such as what each study participant should wear, how they should be positioned, and how the data should be organized and measured. The software that comes with the body scanner creates automatic lists of linear measurements very quickly, but this is only a fraction of the information that is available from a body scan. So the next step was to look for additional software tools to analyze the data in other ways.

Ashdown and Loker adopted a program that was created for the automotive industry, where 3D scanning is extensively used in design. The program (Polyworks, by Innovmetric) merges into one layer the overlapping data from different camera views. The software also has tools that can be used to patch holes in the scan, so that linear, surface area, slice area, and volume measures can be made of the body. Finally, several 3D visualization options are available so that users can view the body scan as a smooth surface, points, or slices, and can rotate, reposition, and zoom in to critical fit areas.

New ways to visualize and measure misfit are also made possible by this software. In the past we could only look at the garment from the outside and see where it stretches or sags. Now we can actually measure the space between the outside of the body and the inside of the clothing — the very essence of fit!

Four kinds of measurements reveal much about body shape and clothing fit: volumes, surface areas, linear measures (circumferences), and slice areas (cross sections). (Image: Deviron, LLC)

In their first major project Ashdown and Loker collected body scan data on women from an apparel company’s specific target market. Subjects were scanned to capture their body size and shape, and were scanned again wearing the best-fitting pants from the company’s size range. The measurement differences between the body and pant scan define the level of fit or misfit. This is a new kind of information that can be used to evaluate the company’s sizing system and to propose changes that will fit more of the target market, i.e., increase the number of people that the company wants as customers who can find garments that fit well.

New sizing systems and grade rules may be recommended based on the results of this study. The goal of the research is to provide a model process and mathematical approach to improve fit for individual companies based on their target markets and current sizing systems.

The Lycra scanning suit was designed to be worn over the subject’s ordinary underwear to make the scan process more comfortable. (Image: University Photography)
For the first time, we can visualize and measure the space between the body and clothing and truly capture the fit of the garment. (Image: Adriana Petrova)


Consumer Reactions


Commercial applications of body scanning — mass-customized clothing, improved ready-to-wear sizing systems, and virtual try-on — will not be viable if consumers do not want to be scanned. We asked the women scanned in our study about their comfort and interest in body scanning. We found the answer to be a resounding “yes” for interest and comfort, regardless of size, age, or their satisfaction with the fit of available ready-to-wear pants. Almost all were willing to be scanned again and many were willing to be scanned every year or whenever their weight changed.

Participants were less comfortable seeing their scans as a still or moving picture on the computer screen and least comfortable showing their scans to family and friends. To address this issue, we have pursued some ideas to increase the comfort people have in viewing their own scan. These include abstracting the scan by reducing the number of data points, changing the color and lighting on the scans, and placing several scans together for context.

We also found very positive reactions to commercial applications using body scan data. Participants found the virtual try-on application more appealing than custom-fit clothing or patterns, size prediction, or personal shopper applications. They also selected virtual try-on as the most likely to influence them to buy more clothing on the Internet. Virtual try-on, custom-fit clothing, and personal shopper were rated highest in helping to find clothing that looks good on the body, and custom-fit and size prediction were rated highest in helping to find clothing that fits. Participant confidence was also extremely high in the applications of body scan data as an effective way to obtain body measurements, as an effective means to obtain good fit, and in trusting an online screen image of their own body more than an idealized body shape.

The participants in the study found the virtual try-on application of body scan data most appealing. (3D Models: WPG. Scan Data: Cornell Body Scan Research Group)

Research still needs to be conducted on men and people of other ages, though our results suggest that consumers are willing to have their bodies scanned. If the same results are found with future studies, other problems may remain: How easy will it be to change the ways consumers shop and buy clothing? Will they be willing to view their clothed body scan on a computer screen instead of touching and trying on actual garments? Much work remains.

A 3D body scan shows the body in a new way and can be uncomfortable to view. Scan subjects may be more comfortable viewing their scans in an abstract format, such as the one on the right, rather than one that captures every detail of the body. (Image: Katherine Schoenfelder)

Advertisements
Categories: Uncategorized
  1. No comments yet.
  1. No trackbacks yet.

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out / Change )

Twitter picture

You are commenting using your Twitter account. Log Out / Change )

Facebook photo

You are commenting using your Facebook account. Log Out / Change )

Google+ photo

You are commenting using your Google+ account. Log Out / Change )

Connecting to %s

%d bloggers like this: