Abstract

Accurate measurement of foot shape feature parameters is extremely important in the process of customized shoemaking. A 3D foot’s depth image collected by second-generation Kinect is used to propose a foot shape feature parameter measurement algorithm. Through 3D reconstruction of foot based on improved interactive closest points algorithm, the coordinate transformation, feature point selection, and B-spline curve fitting algorithm, the foot length, foot width, metatarsale girth, and other foot feature parameters were calculated. The 3D foot measurement system using this algorithm is tested, and the results of multiple measurements have a mean variance of less than 0.3 mm. The average error between the algorithm calculation result and the manual measurement result is less than 0.85 mm. The stability and accuracy of the system meet the requirements of custom shoes. It lays a good foundation for the automation and standardization of customized shoemaking.

Highlights

  • With the improvement of living standards and health awareness, people’s comfort requirements for shoes have increased

  • 2.2 Foot shape 3D reconstruction based on improved interactive closest points (ICP) algorithm The first step of the foot shape measurement is to perform image stitching on each frame of depth image captured by the Kinect camera, that is to rotate and translate other frame images into the space of the first frame image, let the same physical points coincide and remove noise points

  • Repeating the above experiment 50 times for different two-frame depth images, the traditional ICP algorithm achieves an overlap of 41.3 times on average, and the improved ICP algorithm achieves an overlap of 30.1 times on average, and the stitching speed is increased by 27.1%

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Summary

Introduction

With the improvement of living standards and health awareness, people’s comfort requirements for shoes have increased. Lee et al [11] of Seoul the National University adopted the stereo vision method for foot shape 3D scanning They used 12 PC cameras to scan and photograph, used feature point matching to estimate the depth of each point on the foot, and made a 3D reconstruction. The LSF-390 foot 3D scanner system of the Stereo3D Technology Co., Ltd. in China [14] adopted a multi-view laser light path design to complete the foot data scanning within 10 s. It obtained point cloud data and automatically extract more than 50 foot parameters. The measurement system proposed in this paper is a preferred method for measuring 3D foot shape

Foot shape scanning system based on Kinect
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