Parametric prediction of garment hood silhouette

What is it about?

This study proposes a predictive framework built on a test stand derived from ISO anthropometric data and 560 simulations performed by systematically varying six construction parameters of a two‑seam hood across 20 plain‑weave virtual fabrics. A radial parameterisation captured the silhouette with 32 parameters in front, side and top views, yielding a structured database of 17,920 values. Regression models using construction dimensions, density and bending stiffness predicted these parameters and were embedded in a ready-to-use parametric CAD drawing for instantaneous graphical forecasting. Physical validation with a 3D‑printed stand and real fabrics showed that 87 % of the observed contour length fell within the prediction band. This study was supported by the Russian Science Foundation under Project № 25-11-00022 ‘A technology of testing textile materials in a virtual environment for 3D modeling of clothes’.

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Why is it important?

Virtual prototyping of clothes relies on iterative trial‑and‑error simulation when searching for a desired silhouette, which wastes time, energy and computing resources. Hoods are a case in point: their draped form depends on complex interactions among construction, material and the wearer’s head and therefore cannot be predicted from the pattern alone.

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