Classification of young males’ shoulder shapes based on cross-sectional morphological characteristics

This paper focused on the different characteristics of shoulder cross-section curves closely related to shape subdivide shapes. In this paper, 213 young college male students aged 18-26 were selected measure data with three-dimensional body scanner. With help imageware12.0 and matlabr2012b software, which could be used classify shapes extracted, method subdividing curvature radius characteristic points curve ratio sagittal frontal diameter was established. K-means clustering through dynamic clustering, optimal classification number determined 4 categories by variance analysis, differences each quantified; comparing section, change section further qualitatively described.