Page 120 - Anthropometry, Apparel Sizing and Design

National size and shape surveys for apparel design 83

3.6 Future trends

During the last 20years, there has been a particular focus on the generation of one-
dimensional data from 3-D anthropometric surveys. Three-dimensional static data
can do much more: it can, as seen in Section 3.3.3, earlier, dramatically improve the
process of design and development across the supply chain, enhancing the shape, size,
and fit of clothing. However, despite these growing applications, it has been suggested
that “a perfect suit is more than static data” (Meixner and Krzywinski, 2011).
There is growing interest in creating and capturing dynamic scan data, that is, data
from a subject whose movements range between mild and extreme activities, such as
walking and skiing. Initial developments—using captured scan variations and shape
analysis tools—led to animated body scans (e.g., Ruto, 2009). Further research, using
an anatomically correct 3-D scan, has been created with movements relevant to high-
performance sport (e.g., cycling), where different poses can be used to construct 2-D
patterns from 3-D scans for close-fitting garments (Meixner and Krzywinski, 2011),
while other work explored the 3-D scanning process as a tool to help predict cycling
performance (Luke, 2016).
Notwithstanding these 3-D scan developments, interest in 4-D temporal capture is
growing (e.g., Cloth Cap). This research describes new techniques to greatly simplify
the process of virtual try-on. The researchers used 4-D movies of people (recorded
with a 4-D high-resolution scanner from 3dMD), which enabled automatic transfer
of 3-D clothing to new body shapes (Black et al., 2017; Pons-Moll et al., 2017).
The approach is to “scan a [moving] person wearing a garment, separate the clothing
from that person, and then render it on top of a new person” (Black et al., 2017). The
figure in the succeeding text illustrates how “cloth cap” supports a range of applications
related to clothing capture, modeling, retargeting, reposing, and try-on (Fig. 3.8).
The full impact of these developments on future size and shape surveys is not yet
known, but with four-dimensional, real-time scanning technologies becoming avail-
able, it may be that survey databases will be compiled, not only with a range of

Fig. 3.8 Cloth cap. From left to right: (1) An example of 3-D textured scan that is part of a 4-D
sequence. (2) The multipart aligned model, layered over the body. (3) The estimated minimally
clothed shape (MCS), under the clothing. (4) The body made fatter and dressed in the same
clothing. (5) This new body shape posed in a new, never seen pose (Pons-Moll et al., 2017).