Purpose

This study focused on how to realize automatic recognition of young women's neck-shoulder shape based on the front and side images.

Design/methodology/approach

The reverse engineering software was used to measure the body sizes of the neck-shoulder part based on the young women's three-dimensional (3D) point cloud data, and the important parameters closely related to the neck-shoulder shape were determined. The neck-shoulder shape of the subjects was classified to establish the classification rules. Then, based on the front and side images, the human body contour was extracted by Matlab, and the data required for neck-shoulder shape classification were obtained by identifying the feature points.

Findings

Through the cluster analysis based on the shoulder angle, back angle, shoulder depth/width ratio and armpit depth/width ratio, young women's neck-shoulder shape was divided into four categories, namely round wide shoulder, flat narrow shoulder, round drop shoulder and hunchback flat shoulder. The neck-shoulder shape could be automatically recognized based on the established classification rules and two-dimensional (2D) body measurement method, with an accuracy rate of 90%. The neck-shoulder shape automatic recognition system constructed based on this method is effective.

Originality/value

This study proposed a simple neck-shoulder automatic recognition method based on the 2D body images. This approach can be extended to other group of human body or other parts of the body.

中文翻译：

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基于2D图像的颈肩人体形状自动识别与3D建模

目的

本研究的重点是如何实现基于正面和侧面图像的年轻女性颈肩形状的自动识别。

设计/方法/方法

利用逆向工程软件，基于年轻女性三维（3D）点云数据测量颈肩部位的体型，确定与颈肩形状密切相关的重要参数。对受试者的颈肩形状进行分类以建立分类规则。然后，基于正面和侧面图像，通过Matlab提取人体轮廓，通过识别特征点得到颈肩形状分类所需的数据。

发现

通过基于肩角、背角、肩深宽比和腋窝深宽比的聚类分析，将年轻女性的颈肩形状分为圆宽肩、平窄肩、圆落肩和圆肩四类。驼背平肩。根据建立的分类规则和二维（2D）人体测量方法，可以自动识别颈肩形状，准确率达90%。基于该方法构建的颈肩形状自动识别系统是有效的。

原创性/价值

本研究提出了一种简单的基于二维人体图像的颈肩自动识别方法。这种方法可以扩展到人体的其他群体或身体的其他部位。