Title :
Foot shape classification using 3D scanning data
Author :
Lee, Yu-Chi ; Chao, Wen-Yu ; Wang, Mao-Jiun
Author_Institution :
Dept. of Ind. Eng. & Eng. Manage., Nat. Tsing Hua Univ., Hsinchu, Taiwan
Abstract :
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.
Keywords :
database management systems; ergonomics; footwear industry; pattern classification; pattern clustering; principal component analysis; production engineering computing; 3D foot anthropometric data; 3D foot anthropometric database; 3D scanning data; CNS 4800-S1093 sizing system; K-means cluster analysis; K-means clustering; Taiwanese male; ball circumference; ball-of-foot length; foot breadth; foot dimension; foot length; foot shape classification; foot sizing system; footwear production; heel breadth; instep circumference; instep height; male right foot scanning image; navicular height; principle component analysis; shoe last design; size number; toe 1 angle; toe 5 angle; toe height; Aging; Eigenvalues and eigenfunctions; Ergonomics; Foot; Footwear; Principal component analysis; Shape; 3D foot dimensions; Foot shape classification; clustering analysis; sizing system;
Conference_Titel :
Network of Ergonomics Societies Conference (SEANES), 2012 Southeast Asian
Conference_Location :
Langkawi, Kedah
Print_ISBN :
978-1-4673-1732-0
DOI :
10.1109/SEANES.2012.6299553