Journal of Fashion Technology & Textile EngineeringISSN: 2329-9568

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Three Dimensional Shapes Analysis for Digital Fashion: Relation among Women's Trunk, Breast, and Abdomen

A novel method of analyzing body shapes of people based on three-dimensional (3D) measurements is proposed. The method is to analyze the body shape by combining analysis results of body parts in order to avoid size and posture affecting the results. To this aim, our previous studies have analyzed the trunk, breast, and abdomen of about 500 Japanese women and extracted their shape factors by combining a body shape model and a principal component analysis. The model describes the trunk of a subject with 750 control points on a B-spline surface normalized by seventeen landmarks and enables us to treat the 3D body shape mathematically, including calculation of average shape. The extracted shape factors comprised six of the trunk, four of the breast, and four of the abdomen. An interpretation of the factors was also performed. The relation among 3D shapes of the trunk, breast, and abdomen is examined in this paper. Component scores of the 536 subjects and interpretations of the fourteen shape factors are used. A correlation matrix and a correlation diagram evaluate the relation of sixty-four pairs of shape factors between the different body parts. The average shapes of the subjects that are classified by the scores illustrate/express the difference in 3D shape of each pair of shape factors. Fifteen of the pairs with correlation coefficients (r) of more than 0.30 in absolute value are focused on and discussed. As a result, two of the pairs, reflecting breast height and degree of obesity, were found to have correlation coefficients sufficiently high (r=0.81,-0.53 respectively) and have similar interpretations. On the other hand, twelve of the fourteen factors have different meanings. This implies that different parts of the body have different shape factors and twelve or more parameters are necessary when treating the 3D shape in a simple way.

In addition, some of the other thirteen pairs show tendencies of the 3D body shapes of the subjects. It has been confirmed that the shapes of body parts tend to change with posture, the shape of other parts, age, stature, and BMI. For instance, the level of the shoulder slope appears to affect the appearance of the breast. This paper also summarizes our series of studies on body shape analysis. Necessity, generalizability, limitation of the presented method, and application to other body parts are discussed.

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