Ramblemuse Touch Points

To date, the internet and technology have had some major impacts on the where and when of shopping for clothes but have not fundamentally changed the process. What existed before as catalog shopping pretty much transferred to web-based catalogs of clothes and shopping online. The process became more convenient, the ability to search and compare improved, but the process has still been an incremental improvement on what could previously be done via physical mail and phone calls. Now, however, we are on the edge of seeing the convergence of several technological developments creating a revolutionary and fundamental change in the clothing industry.

The first big change comes in both having personal fit data and in better understanding the fitting needs of an entire population segment. The article Computerized Female Form For Designers describes an effort to measure and statistically characterize the torso shapes of a diverse sampling of Japanese women.

The team took a close look at the bodies of 560 Japanese women aged from 19 to 63 years using laser metrology to map “control points” at specific sites on the women’s trunks. They could then fit this data to a generic 3D trunk model in the computer and fit the control points to it to build up a database of body shapes.

They then applied statistical analysis to the data employing principal component analysis and cluster analysis to classify trunk characteristics into five different types. Each depends on slimness or otherwise, breast size and angle, neck type, and shoulder slope. They obtained five classes of body shape which they say represent the majority of trunk shape among Japanese women.

A 2005 article in Science Daily noted that Pacific Northwest National Laboratory (PNNL) had won an award for development and commercialization of a three-dimensional body scanner. That scanner development effort was being applied by Intellifit to determining fit for clothing. At this point, Intellifit is putting scanning booths into malls and store. Based on radio frequency scanning, a scan can be done through clothing in 10-15 seconds, measuring 200,000 points on the body that are then boiled down into a couple of hundred body measurements. The scans require about 1/350^th the power of cell-phone emissions. According to the information they provide in videos and other data, Intellifit is working with clothing manufacturers to database clothing size characteristics. These can be used along with personal scan data to steer a consumer to clothing that fits their body according to their shape and sizing preferences. For the consumer, this means being taken directly to clothing that fits their shape over multiple measurements rather than the hit or miss process of choosing one measurement and trying on the clothing to see if the garment works in practice.

For designers and manufacturers, a database of depersonalized measurement data could be used statistically, as with the Japanese study, to characterize and classify body shapes and their frequency of occurrence within the population. Having this data along with a means of steering customers can motivate clothing designers and manufacturers to more precisely target and market to previously under-served consumer needs. In other words, marketing not just to the average consumer shape but to the tail of a distribution or to multiple modes of a distribution of shape needs. There’s the classic example of a bimodal distribution in which the average value may hardly exist in the population.

The next big technology change comes in presentation. Here we see a merging of improved sensors to detect movement, improved displays, and much greater computational capabilities to render 3D images. The combination allows us to computationally augment reality. As an example of the new display capabilities, Andrew Nusca has recently blogged about Intel’s augmented reality digital display. Such display capabilities can be combined with the motion sensor and virtual rendering capabilities displayed in Cisco’s video, The Future of Shopping.

Finally, companies like Zugara carry this back to web shopping with capabilities such as the webcam social shopper. Your own web camera is combined with motion detection and rendering capabilities to create a virtual dressing room.

A report on research and teaching under the direction of Young-A Lee at Iowa State University lends further perspective on the interplay between virtual reality and real life clothing design.

“We’re seeing retailers use the concept of Second Life to test prototypes of clothing, shoes and other products” Lee said. “A person’s body scan data is made into an avatar, and this avatar is the real presentation of him or herself and carries each individual’s virtual identity within the virtual environment such as Second Life. Then, they can shop at stores, where a manufacturer may be testing out a new product to see if it is popular [within Second Life]. If it is, they may go on to actually produce the piece of clothing, shoes, or whatever they try out.”

Further Reading

Devarajan, Priya: 2004. Validation of ‘Female Figure Identification Technique (FFIT) for Apparel’ Software. Journal of Textile and Apparel, Technology and Management, 4(1), <http://www.tx.ncsu.edu/jtatm/volume4issue1/articles/Istook/devarajan_full_106_04.pdf>.

Explore Cornell. 3D Body Scanner. Accessed 10 June 2010. <http://ecommons2.library.cornell.edu/web_archive/explore.cornell.edu/scene0037.html?scene=The%203D%20Body%20Scanner>.

Lim, Hosun, Cynthia L. Istook, and Nancy L. Cassill: 2009. Advanced Mass Customization in Apparel. Journal of Textile and Apparel, Technology and Management, 6(1). <http://www.bioresourcesjournal.com/index.php/JTATM/article/viewFile/414/360>.

Nakamura, Kensuke, and and Takao Kurokawa: 2009. Analysis and classification of three-dimensional trunk shape of women by using the human body shape model. Int. J. Computer Applications in Technology, 34, 278-284. <http://inderscience.metapress.com/link.asp?id=ev4w6150k1137r18>

Polvinen, Elaine. Virtual Fashion Technology (blog). Accessed 10 June 2010. <http://fashiontech.wordpress.com/>