Foot shape prediction using elliptical Fourier analysis

Ge Wu, Duan Li, Pengpeng Hu, Yueqi Zhong, Ning Pan

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)

Abstract

In this paper, a new method was proposed to establish the relationship between three-dimensional (3D) foot shapes and their two-dimensional (2D) foot silhouettes, through which a complete 3D foot shape can be predicted by simply inputting its two 2D silhouettes. 3D foot scans of 80 participants were randomly selected as the training set, and those of another 20 participants were used as the testing set. Elliptical Fourier analysis (EFA) and principle component analysis (PCA) were adopted to parameterize the 3D foot shapes. A linear regressive model was then developed to predict the 3D foot shape with the foot silhouettes. Experiment results indicated individual 3D foot shape can be predicted with a mean error between 1.21 and 1.27 mm, which can provide enough accuracy for the fit evaluation of footwear.
Original languageEnglish
Pages (from-to)1026-1037
Number of pages12
JournalTextile Reseach Journal
Volume88
Issue number9
DOIs
Publication statusPublished - 17 Feb 2017
Externally publishedYes

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