Authors:

Carol MCDONALD 1, Emma SCOTT 2, Fatma BAYTAR 3, Susan ASHDOWN 3, Gerald RUDERMAN 4

1 Gneiss Concept, USA;
2 Fashion Should Empower Research Group, Canada;
3 Cornell University, USA;
4 Zdoit, USA

DOI:

https://doi.org/10.15221/24.17

Full paper:

PDF

Keywords:

3D body scanning, 3D body processing, apparel fit, posture, posture descriptors

Abstract:

The foundations of good fit in patternmaking are identified as grain/wale, line, ease, balance and set. The interaction of these factors with themselves and the human body establishes the body-to-garment relationship understood to be ‘fit’. Posture is a critical component of this relationship. Posture also impacts the balance and set of the garment, both in stationary and active poses. The skeletal joints distinguishing posture provide the understanding of the garment suspension points and direct the distribution of ease and flow of the garment from these points.
During large-scale study of scanned human body data, it is common practice to normalize subject posture and focus on subject shape. This practice has proven effective for ergonomic use cases, but problematic for apparel-related practice where the body must be understood in relationship to interaction with garment materials and design. Often, posture and shape are intrinsically related, and separation invalidates apparel use-case results. Varying degrees of head thrust, shoulder rotation, pelvic tilt, kyphosis, lordosis, and varus or valgus knee alignment all change the body-to-garment relationship. A previous posture study has identified placement, alignment, rotation, curvature, and symmetry (PARCS) as descriptors for body region relationships related to posture and pose.
In this paper, we use PARCS descriptors to consider metrics for describing the aspects of posture related to the body-to-garment relationship. These descriptors could be used to reassess vast accumulated 3D body data sets for posture-inclusive shape studies better suited to apparel practice. Recognizing where posture exists outside a baseline ‘normalized’ range is essential for providing good apparel fit for the population. Studies to support where skeletal posture and body shape are intrinsically intertwined will further such efforts.

How to Cite (MLA):

McDonald, Carol et al., "Metrics for Including Posture and Body-Shape Variation in Scan Databases for Apparel Practice", 3DBODY.TECH Journal, vol. 1, Oct. 2024, #17, https://doi.org/10.15221/24.17.

Presentation:

VIDEO availble in proceedings

Details:

Volume/Issue: 3DBODY.TECH Journal - Vol. 1, 2024
Paper: #17
Published: 2024/10/30
Presented at: 3DBODY.TECH 2024, 22-23 Oct. 2024, Lugano, Switzerland
Proceedings: 3DBODY.TECH 2024 Proceedings

License/Copyright notice

Copyright © 2024 by the author(s).
This work is licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
The papers appearing in the journal reflect the author's opinions. Their inclusion in the volumes does not necessary constitute endorsement by the editor or by the publisher.

Note: click the + on the top left of the page to open/close the menu.