Foot shape prediction using elliptical Fourier analysis
Source abstract
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.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Lower Extremity Biomechanics and Pathologies · Optical measurement and interference techniques · Diabetic Foot Ulcer Assessment and Management
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
College of Textiles, Donghua University, Shanghai, China
Key Lab of Textile Science and Technology, Ministry of Education, China
Department of Biological and Agricultural Engineering, University of California at Davis, CA, USA
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