Human surface morphology representation and shape subdivision driven by space vector on female “waist-to-thigh” zone

Abstract

Purpose

The human body has the same basic size data but has different surface morphology, resulting in the unfitness even under the same size specification. The purpose of this study was to solve the local fitness problems by representing and quantifying the human surface morphological difference.

Design/methodology/approach

Firstly, the 3D point cloud for 323 female students was scanned, and the cross-section layers of the “waist-to-thigh” zone were determined. Secondly, the space vector based on the space Euclidean distance was extracted to represent and quantify the surface morphological difference. And the Principal Component Analysis and K-means were adopted to subdivide the target zone. Thirdly, the pattern based on the subdivision results and surface flattening was generated. Additionally, the fitness was evaluated by the subjective and objective assessments, separately.

Findings

The space vector could represent and quantify the shape morphology of the “waist-to-thigh” zone. It had successfully achieved the human body subdivision and corresponding pattern generation for the “waist-to-thigh” zone. And the pattern based on the shape subdivision and surface flattening of the space vector could effectively improve the wearing fitness. Particularly in the waist and crotch area of trousers, the obvious wrinkles had been solved because the space vector is more in line with the shape morphology characteristics.

Originality/value

The proposed method could represent and quantify the difference in human surface morphology in a 3D manner. It solved the unfitness problem caused by the same body size but different shape surface morphology. And it will contribute to the fitness improvement of the trousers.