基于二维图像的青年女性颈肩部形态自动识别

为实现青年女性颈肩部形态的自动识别,首先基于202名在校青年女性的三维点云数据,测量了15个颈肩部形态相关参数,通过分析确定出离散程度较大的形态参数,包括肩斜角、背入角、肩矢额径比和腋下矢额径比;然后结合这4个重要体型参数,对青年女性颈肩部形态进行细分并建立各类体型的分类规则;最后基于青年女性正面与侧面二维照片,通过提取人体轮廓和识别特征点获得颈肩部体型分类所需参数,根据体型分类规则实现颈肩部形态的自动识别。结果表明:青年女性颈肩部形态可分为4类,即圆宽肩体、扁窄肩体、圆落肩体、驼背扁肩体,分别占样本总数的25.53%、23.94%、25.59%和23.94%;通过对40名测试样本进行基于正、侧面二维照片的颈肩部形态自动识别验证,准确率达到90%,说明基于本文方法构建的颈肩部体型自动识别系统是有效的。

Automatic identification of young women's neck-shoulder shapes based on images

In order to facilitate the automatic identification of young women's neck-shoulder shapes, 15 neck-shoulder shape parameters of 202 young women were measured in the form of three-dimensional point cloud data, and the parameters with a large degree of dispersion were determined through analysis, including the shoulder angle, back angle, shoulder depth/width ratio and armpit depth/width ratio. Combined with these four important body parameters, the neck-shoulder shape of young women was classified following the established classification rules. Based on the front and side images, the parameters required for neck-shoulder shape classification were obtained by extracting the human body contour and identifying the feature points, and the automatic identification of the neck-shoulder shape was achieved according to the body type classification rules. The results show that young women's neck-shoulder shape is divided into four categories, namely round wide shoulder, flat narrow shoulder, round drop shoulder, hunchback flat shoulder, accounting for 25.53%, 23.94%, 25.59% and 23.94%, respectively, of the total sample. The identification of the neck-shoulder shape based on the front and side images of 40 test samples is verified, and the accuracy ratio reaches 90%, indicating that the neck-shoulder shape automatic identification system constructed using this method is effective.