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When wearing compressive garments, the tissue of the human body is altered in relation to its natural shape by the properties of the applied material and by the pattern construction used.
To check the fit of garments, both construction and selected materials can be virtually simulated in 3D on avatars in corresponding CAD programs before fabrication.
The software Blender allows the modelling of an avatar and to generate in respective to the different tissue zones with their specific properties to adjust them with soft body physics according to the testing of real soft tissue but the models in Blender are mainly using linear springs.
In recent years, the demand for accurate and efficient 3D body scanning technologies has increased, driven by the growing interest in personalised textile development and health care. This position paper presents the implementation of a novel 3D body scanner that integrates multiple RGB cameras and image stitching techniques to generate detailed point clouds and 3D mesh models. Our system significantly enhances the scanning process, achieving higher resolution and fidelity while reducing the cost, time and effort required for data acquisition and processing. Furthermore, we evaluate the potential use cases and applications of our 3D body scanner, focusing on the textile technology and health sectors. In textile development, the 3D scanner contributes to bespoke clothing production, allowing designers to construct made-to-measure garments, thus minimising waste and enhancing customer satisfaction through fitting clothing. In mental health care, the 3D body scanner can be employed as a tool for body image analysis, providing valuable insights into the psychological and emotional aspects of self-perception. By exploring the synergy between the 3D body scanner and these fields, we aim to foster interdisciplinary collaborations that drive advancements in personalisation, sustainability, and well-being.
The process for the production of customized bras is really challenging. Although the need is very clear, the lingerie industry is currently facing a lack of data, knowledge and expertise for the realization of an automated process chain. Different studies and surveys have shown, that the majority of women wear the incorrect bra size. In addition to aesthetic problems, health risks such as headaches, back problems or digestive problems of the wearers can result from this. An important prerequisite for improvements is the basic knowledge about the female breast, both in terms of body measurements and different breast shapes. The current size systematic for bras only defines a bra size by the relation between bust girth and underbust girth and standardized cup forms do not justice to the high variability of the human body. As the bra type shapes the female breast, basic knowledge about the relation of measurements and shapes from the clothed and the unclothed breast is missing.
In the present project, studies are conducted to explore the female breast and to derive new breast-specific body measurements, different breast shapes and deformation knowledge using existing bras.
Furthermore, an innovative process is being developed that leads from 3D scanning to individual and interactive pattern construction, which allows an automatic pattern creation based on individual body measurements and the influence of different material parameters.
In the course of the presentation, the current project status will be shown and the future developments and project steps will be introduced.
Today's pattern making methods for industrial purposes are including construction principles, which are based on mathematical formula and sizing charts. As a result, there are two-dimensional flats, which can be converted into a three-dimensional garment. Because of their high linearity, those patterns are incapable of recreating the complexity of the human body, which results in insufficient fit. Subsequent changes of the pattern require a high degree of experience and lead to an inefficient product development process. It is known that draping allows the development of more complex and demanding patterns, which corresponds more to the actual body shape. Therefore, this method is used in custom tailoring and haute couture to achieve perfect garment fit but is also associated with time.
So, there is the act of defiance to improve the fit of garments, to speed up production but maintain a good value for money. Reutlingen University is therefore working on the development of 3D-modelled body shapes for 3D draping, considering different layers of clothing, such as jackets or coats. For this purpose, 3D modelling is used to develop 3D-bodies that correspond to the finished dimensions of the garment. By flattening of the modelled body, it is then possible to obtain an optimal 2D Pattern of the body. The comparison of the conventional method and the developed method is done by 3D simulation.
Finally, the optical fit test is demonstrated by the simulated basic cuts, that a significantly better body wrapping through the newly developed methodology could be achieved. Unlike in the basic cuts, which were achieved by classical design principles have been created, only a few adjustments are necessary to obtain an optimized basic cut. Also, when considering the body distance, it is shown that the newly developed basic patterns provide a more even enclosure of the body.
Patterns are virtually simulated in 3D CAD programs before production to check the fit. However, achieving lifelike representations of human avatars, especially regarding soft tissue dynamics, remains challenging. This is mainly since conventional avatars in garment CAD programs are simulated with a continuous hard surface and not corresponding to the human physical and mechanical body properties of soft tissue. In the real world, the human body’s natural shape is affected by the contact pressure of tight-fitting textiles. To verify the fit of a simulated garment, the interactions between the individual body shape and the garment must be considered. This paper introduces an innovative approach to digitising the softness of human tissue using 4D scanning technology. The primary objective of this research is to explore the interactions between tissue softness and different compression levels of apparel, exerting pressure on the tissue to capture the changes in the natural shape. Therefore, to generate data and model an avatar with soft body physics, it is essential to capture the deform ability and elasticity of the soft tissue and map it into the modification options for a simulation. To aim this, various methods from different fields were researched and compared to evaluate 4D scanning as the most suitable method for capturing tissue deformability in vivo. In particular, it should be considered that the human body has different deformation capabilities depending on age, the amount of muscle and body fat. In addition, different tissue zones have different mechanical properties, so it is essential to identify and classify them to back up these properties for the simulation. It has been shown that by digitising the obtained data of the different defined applied pressure levels, a prediction of the deformation of the tissue of the exact person becomes possible. As technology advances and data sets grow, this approach has the potential to reshape how we verify fit digitally with soft avatars and leverage their realistic soft tissue properties for various practical purposes.
For a holistic assessment of the interaction between the human body and tight fitted clothing, it is necessary to consider the mechanical properties of the body. Default avatars in CAD software are usually solid and do not take this interaction into account. For this purpose, a solid avatar is converted to a deformable one by using the soft body physics implementation in the simulation program Blender. The fit of a 3D garment on both avatars are compared, which allows a first evaluation of the differences between these approaches.