Kensuke Nakamura

Analysis and classification of three-dimensional trunk shape of women by using the human body shape model

This paper proposes a new method for extracting shape components of the trunk of women from three dimensional measurements and tries a classification of the trunk shapes. Subjects in this study are 560 Japanese women, ranging in age from 19 to 63 years. First, the authors describe three-dimensional (3D) trunk shape using the control points given by fitting the human body shape model to 3D measurements of the subjects and reduce the number of the control points to be suited for statistical analysis based on correlation strength. The principal component analysis is applied to the shape data or the reduced set of the control points. Then, the authors interpret trunk shape components by combining factor loading map and averaged shape figures. Finally, the authors try to classify the trunk shape of Japanese women by means of the cluster analysis of component scores of the above results.

Description of human body shape using an isomorphic polygon

A novel polygon model describing human body shape is developed. Firstly, a method of expressing an arbitrary point on a polygon mesh using the UV plane is proposed. An isomorphic feature of the model enables us to fit the polygon model to three-dimensional (3D) measurements by means of the least square method. Secondly, in order to optimise the model structure, vertices of the model are allocated to trunk shape based on multiple sets of 3D measurements of Japanese women. Finally, the experimental results show that the derived generic model consisting of 1,087 vertices can reconstruct the original shapes with the average error of 1.19 mm, sufficient for practical use.

Simulation of brassiere-wearing figures

This article proposes a simulation method that combines a three-dimensional shape model of a human body with the genetic algorithm (GA) for estimating shape change of the breasts by wearing a brassiere. The model can describe trunk shape of any female with 750 control points for fitting the surface to many 3D points on the trunk surface. Because the model structure is common among women, their body shapes can be statistically analysed by using the control points. First, we related naked 230 breasts of 115 Japanese women with those wearing a full-cup brassiere through the multi-regression analysis. In this process, we searched the best regression formulas among a plethora of combinations of terms, or coordinates of the 49 control points on the naked models through the GA. Second, the regression formulas obtained above were applied to another 22 naked breasts to estimate their brassiere-wearing shape. Visual and numerical evaluation of the simulated shape revealed that this method could predict brassiere-wearing breast shape based on naked ones and could be expected to serve in a design process and for sales without the need to try on.