Standards Development

Scope

This technical specification describes a method for analysing 3D body scan data which can be used to establish a range of body shapes for applications in clothing fit and design.

Purpose

To appreciate the importance of body shape in the clothing industry, is to understand the infinite number of combinations of the main measurements that identify the human body.

This is the result of evolution and intermingling among populations over time, geographical factors, eating habits, lifestyles and numerous other factors. At present all types of garment are necessarily based on a combination of measurements selected to represent a given normotype, with size charts and body conformations that represent a manufacturer’s standard for a given market segment.

There are no absolute parameters, but rather a combination of measurements selected on the basis of statistical population data.

To identify a given normotype by merely defining a series of measurements is not sufficient. Knowledge of the body shapes associated with those measurements is required, is to understand how these body shapes vary. For example, garment pattern design techniques may change significantly.

- One female hip girth may be associated with very prominent buttocks and narrow hips, or less prominent buttocks and wider hips, or flatter buttocks and curvier hips, etc.

- The same bust girth may apply to a person with very large breasts, or medium or even small breasts,

- For a given shoulder width, there may be differences in shoulder slope, high shoulders, regular shoulders or low shoulders, open or closed shoulders.

- For the same height, there may be considerable variation between populations in terms of body segment combinations, so we may find subjects with long legs and a short body or vice versa and more regular subjects.

Many more examples exist, and each can translate into different garment pattern designs to take into account body shapes. Notwithstanding these variations, when a manufacturer produces garments for a given market, they should first, either access or conduct an in-depth study into the anthropometry of the population, not only in terms of body dimensions but also in terms of body shapes.

National, regional or company anthropometric surveys using 3D body scanners are increasingly important as they provide, in addition to body dimensions other vital information on body shapes in a population through 3D imaging.

However, the majority of the clothing industry and current standards are limited to information for body size, which does not take account of the variety of different body shapes within different populations. 3D body shape data enables companies to create products that more closely represent the distribution of posture, pose, balance and shape, as well as size, within their target populations.

The inclusion of shape provides an opportunity to produce better-fitting clothes and has the potential to help reduce the volume of poorly fitting garment returns, as well as increase customer satisfaction and contribute to a more sustainable industrial practice.

The application of shape data in the clothing industry is growing and opportunities exists to create body shape libraries, which can, not only ensure the reproduction of 3D target shapes for the creation of average avatars, but also have the potential to:

- ensure the shape of fit mannequins and support the selection of physical fit mannequins

- 3D garment design and development, and the generation of 3D block, style and graded patterns

- provide opportunity to update label pictograms to assist consumers in making a choice of garment for their body shape as well as size

- enhance the process of digital fitting for designers and retail customers.

Many companies are beginning to use body shape data but there is no technical guide or method to help companies analyse and/or create average body shape data. This technical Specification outlines a method that can be used to stable shapes either for a national population or for a specified target market within a population.