利用三维扫描数据进行足形分类

Yu-Chi Lee, Wen-Yu Chao, Mao-Jiun Wang
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引用次数: 13

摘要

收集三维足部人体测量数据并将其分类为几种足部形状。使用了一个包含1835张男性右脚扫描图像的三维足部人体测量数据库。研究对象年龄从18岁到60岁不等。采用三维足部扫描仪采集足长、足球长、外足球长、足宽、足跟宽、足周长、脚背围、趾高、舟高、脚背高、趾1角、趾5角等12个足部尺寸。采用主成分分析(PCA)和k均值聚类分析对男性受试者的足型进行分类。主成分分析结果表明,选择足宽、足长和舟高作为三个主要成分。3个主成分对总方差的解释率为72.96%。使用K-means聚类可以将男性受试者的脚分为6种脚类型。此外,还为台湾男性开发了一种新的足部尺码系统。与现有的CNS 4800-S1093上浆系统相比,新上浆系统可以减少尺码数,并提供更新的足部尺寸。因此,制造商可以将这些结果应用于鞋楦设计和鞋类生产,从而获得更好的健身效果和更低的成本。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Foot shape classification using 3D scanning data
3D foot anthropometric data was collected and classified into several foot shapes. A 3D foot anthropometric database which contains 1835 male right foot scanning images was used. The subjects aged from 18 to 60 years old. A 3D foot scanner was used to collect 12 foot dimensions including foot length, ball of foot length, outside ball of foot length, foot breadth, heel breadth, ball circumference, instep circumference, toe height, navicular height, instep height, toe 1 angle and toe 5 angle. The principle component analysis (PCA) and K-means cluster analysis was applied to classify male subjects' foot shapes. The PCA results indicated that foot breadth, foot length and navicular height were selected as three principle components. The percentage of total variance explained by the 3 principle components was 72.96%. The use of K-means clustering can classify male subjects' foot into 6 foot types. In addition, a new foot sizing system was developed for Taiwanese males. Comparing the new sizing system with the current CNS 4800-S1093 sizing system, the new sizing system can reduce the size numbers, and provide updated foot dimensions. Thus, the manufacturer can apply these results for shoe last design and footwear production with better fitness and lower cost.
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