An early version of the virtual try-on concept -- without body scan data -- is now being offered online by Lands' End, Levi Strauss, Lane Bryant, and the Wedding Channel. However, these systems are designed for style selection, not sizing. Here's how it works.

• A customer takes her/his own measurements.
• The online application lists a predetermined set of measurements. The customer selects those that are closest to her/his own.
• In some cases, information about the general body shape is entered, such as small waist, large hips, narrow shoulders, or long torso. Hair style, hair color, facial and other characteristics can also be included.
• The online application develops a general image of the customer’s body shape and displays it on the screen for confirmation or modifications.
• The customer selects clothing styles from the screen and "tries them on" the virtual image.
• The garment is "dressed" onto the virtual customer and then preferred clothing styles are selected for purchase.

When body scan data are introduced into this process, the virtual image will become more realistic and the size selection more accurate. The customers will view their own 3D image (not an idealized model); rotate it to see front, back, and side views; and select the style and size that fits best.

A related application of body scanning is size prediction, in which consumers submit their measurements to a service company which has access to size specifications for many brands of apparel products. The service matches consumers with garments by comparing measurements. Several companies such as My Virtual Model and TheRightSize already offer size prediction, but do not use body scan data.

Body scan data will increase the number and accuracy of measurements used in size prediction. The combination of virtual try-on with size prediction will not only provide consumers with the brands and sizes that fit their measurements and proportions best, but will also let them virtually view garments on their scan and choose the design they like best. This process combines objective fit information with fit preference -- the most realistic way of satisfying customers.