STAGE 3 : Sizing system
6.2 History of full-body scanning, its use in apparel sizing and fit, and anthropometric studies
6.2.1 Early scanners
The first full-body scanner that was widely marketed in the late 1990s was made by Cyberware and was primarily sold to the entertainment industry and military researchers (Robinette and Whitestone, 1994) (seeFig. 6.1). It used stationary sensors and an eye-safe laser as a light source and provided a rotating platform for the person being scanned. The technology was effective, but the scanners were not portable, and their cost was prohibitive for most users. At this stage, neither the usefulness nor the specific procedures of scanning appropriate for apparel research or anthropometric studies were well understood. Cyberware, Inc. was dissolved in 2011.
The next generation of scanners available by the mid-1990s included brands such as Vitronic/Human Solutions, TC2, Hamamatsu, Telmat, Wicks and Wilson, and TecMath (Daanen and Jeroen van de Water, 1998). These scanners were costly but at a level that could be justified for a wider range of research opportunities, and their usefulness was becoming more apparent. They were still relatively large installations and were not optimal for scanning in multiple locations, although some systems could
Fig. 6.1 Early Cyberware scanner with a rotating platform (from Flickr user NIOSH).
be set up in a truck and moved from one site to another. This generation of scanners had multiple sensors placed around the body that allowed the subject being scanned to remain stationary instead of rotating on a platform. They were all similar in that they consisted of a light source, sensing devices, software to assemble the scan from the data from the sensing devices, and software to extract information (generally simple linear measurements) from the assembled scan.
Basic 3-D body scan data from these scanners and from 3-D scanners in general are expressed in anXYZ coordinate space. These scanners captured and plotted points from the surface of the body, generally in a grid density of 2 mm2mm resulting in about 27 points per cm2or about 300,000 points in a scan of an average-sized per-son. The points could be triangulated and surfaced to create a statue-like rotatable image. The systems that had cameras to capture color and texture information gener-ally “wrapped” this information as a separate layer onto the 3-D model.
The volume of the scanning area differed among scan companies but was generally in the range of 2.1 m (height)1.2m (depth)1m (width) and accommodated a standing or seated person. The available scanners differed greatly in the mode of rep-resentation of the scan data on the computer screen, from a simple point cloud to a model with triangulated and surfaced points highlighted with simulated lighting and providing different choices in perspective rules for viewing the model (see Fig. 6.2). The displays also varied in how much postprocessing was applied to the scan data, beyond simply assembling or merging the different camera views. Any scanner creates redundant points, either throughout the surface of the scan (white light scans) or in the overlapping camera views (laser light scans) (seeFig. 6.3). The task of the software developer who generates the program to assemble and justify these redun-dant data points is to create a digital model that will have the same measurements and shape of the complex, organic body. Reducing the scan to essential points will also reduce the size of the file, without losing needed information (seeFig. 6.4). This process can also improve scan visualization.
Generally, these early scanners were marketed as a sophisticated measuring device that could extract a large number of linear measurements and some angle measure-ments automatically from the scan. These measuremeasure-ments (which were based on data taken by manual measuring tools such as tape measures, anthropometers, goniome-ters, and calipers), and not the actual 3-D scan data themselves, were often the focus of the data display. As is frequently the case with new technologies, many researchers did not have a good concept of how to use the actual 3-D scan itself, as 3-D data were unfamiliar.
The measurements that were generated from the scans varied, with some modeled on standard anthropometric practice and some modeled on the measurements made by tailors and the apparel industry. Scanner companies also developed the capability to scan and derive measurements from subjects in seated positions to generate data for the automotive and airline industries. Multiple studies were conducted to verify the reliability and validity of the measurements of the different scanners, comparing auto-matically derived scan measurements with manually taken measurements of the same subjects (Bradtmiller and Gross, 1999;Paquette et al., 2000;Mckinnon and Istook, 2001;Choi and Ashdown, 2010). Studies were also conducted on issues relating to
the subject being scanned, addressing appropriate scan clothing, posture, breathing, and body sway (Brunsman et al., 1997;Mckinnon and Istook, 2002;Daanen et al., 1997a;Kim et al., 2015).
The output of the scanner was dependent on how the scanner and the scan software performed at many different stages of the process (appropriate calibration, reliable data capture by the individual sensing devices, number of sensing devices, reliable and valid integration of data from the multiple sensing devices into a 3-D model, valid location of measurement points [body landmarks], valid combination of on-the-surface and/or spanning of body prominences with the digital “tape measure,” and valid choices on placing circumferential measurements that can either follow the body shape or follow the axis of the torso or limbs or are taken parallel to the floor). How-ever, few studies reported or addressed these issues but only compared the final mea-surements from the scanner and their relationship with some version of corresponding manual measurements. It is understandable that researchers neglected to include this information, as the ability to examine many of these factors was not given to the user.
Fig. 6.2 Screen visualizations, one as a point cloud with body measurement locations indicated with lines and another as a triangulated and surfaced figure. Simulated lighting of the surfaced figure creates shadows that provide a visual reference to the 3-D shape.
Fig. 6.4 Stages in merging and smoothing points, demonstrated on a white light scan image and on a laser scan image.
Fig. 6.3 Point clouds. Multiple points collected by a white light scanner (showing the wave effect) and organized points collected every 2 mm by a laser scanner (showing a slice from the scan with points from overlapping patches, captured by different cameras).
This lack of understanding of the scanning technology ultimately led to misunder-standings of the nature of scan measurements, which at times impeded effective devel-opment of methods of creating and using scan data.
There are two factors in the discussion of the “accuracy” of the scanner measure-ments that were not often discussed or resolved. One is the fact that the human body is an organic form that is in a state of constant change, so no method of measurement will result in identical measurements, even when taken within the same time frame. Mea-surements taken over time will vary even more. Changes in the posture of the person being measured, or in the placement of landmarks, combined with physiological changes (water loss or gain in the body driven by hormonal changes, compression of the spine that occurs throughout the day) result in measurement variation not related to the sophistication of the measuring tool. The other is the fact that the body is mal-leable and compressible, whereas the scan is a digital “statue” of the body. An argu-ment can be made that the digital body created with a properly calibrated scanner is a more reliable object than the body itself; it is the body captured in a certain time and posture, and every measurement taken from the scan (as long as landmarks are iden-tical) will be constant and will relate to one another in a valid manner. If this philos-ophy is adopted, then scan measurements from a calibrated scanner are the “accurate”
value and can form the basis for clothing design and sizing systems in the nondigital real world if chosen and used in a valid manner.
6.2.2 Use of 3-D body scans and data from scans in apparel studies
Early use of scan data focused only on extracted linear measurements from the scans.
Full-body 3-D scanning provided data for anthropometric studies of various populations, body shape analysis based on simple circumferences, extraction of mea-surements as the basis for custom-made clothing, automatic size selection, and the creation of avatars for size selection (Robinette et al., 1999; Bougourd and Treleaven, 2014; Devarajan and Istook, 2004; Hye, 1999; Corcoran, 2004; Lerch et al., 2007).
However, there were also early attempts to use the scans in ways that used more of the complex 3-D data from the scan.Robinette and Whitestone (1992)conducted an early study comparing 3-D head scans of army personnel with 3-D scans of helmets and proposed similar studies to align and merge clothed and unclothed body scans to directly compare clothing-to-body relationships in 3-D (Robinette and Whitestone, 1992). Circumferential slices of such scans provided precise data on the distance of the worn clothing from the body (seeFig. 6.5). Many studies of this nature have been conducted of firefighter gear for which the gap between clothing and body that captures still air can be thermally protective and for cooling vests that rely on contact of the vest with the body surface for conductive cooling (Park and Langseth-Schmidt, 2016;Deng et al., 2018;Branson et al., 2005).
Three-dimensional body scans are also used in the manufacture of dress forms that precisely duplicate the size, shape, proportions, and posture of an apparel firm’s fit model. Most dress forms in the past (except those made for lingerie or swimwear) have
reflected garment shapes instead of body shapes, but this is changing with modern styles and materials that create clothing silhouettes that follow the curves of the body.
Dress forms made from 3-D scans are used in product development and fit analysis (Haber, 2006) (seeFig. 6.6).
Body scans have also been used to examine body shape variation by assessing the 3-D shapes directly; for example, a lingerie company used 3-D scans to visually iden-tify different bust shapes and configurations in the population. Using the method of subjective analysis of the different shapes, designers analyzed which shape variations had an impact on bra fit and made decisions about styles that are optimized for dif-ferent women. Understanding bust shapes also made it possible to choose appropriate fit models for the development of specific styles. This shape analysis, making judg-ments from a visual assessment of the 3-D scan, can be very productive. Other means of sorting the population into shape groups have been developed based on data from 3-D scans using powerful statistical analysis methods (Song and Ashdown, 2011).