Foot measurements from 2D digital images

Xiong, Shuping; Li, Yulin; Zhu, Yi; Qian, Jingxing; Yang, Dong

doi:10.1109/ieem.2010.5674498

Cited by 4 publications

(2 citation statements)

References 2 publications

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“…Xiong et al [ 51 ] presented a computer-aided design (CAD) system for designing custom footwear that automatically extracted the features of a foot, and their method worked basically in three main modules. In sequence, Xiong et al [ 52 ] exhibited an advanced method of obtaining foot measurements from a 2D digital image; it was dependent on the hardware setup system. In [ 53 ], a foot-shape feature parameter measurement algorithm using a second-generation Kinect was implemented, and the authors measured foot length, foot width, metatarsal girth, and other foot parameters using a 3D foot depth image.…”

Section: Background and Related Workmentioning

confidence: 99%

OptiFit: Computer-Vision-Based Smartphone Application to Measure the Foot from Images and 3D Scans

Rafiq

Hoque

Kabir

et al. 2022

Sensors

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The foot is a vital organ, as it stabilizes the impact forces between the human skeletal system and the ground. Hence, precise foot dimensions are essential not only for custom footwear design, but also for the clinical treatment of foot health. Most existing research on measuring foot dimensions depends on a heavy setup environment, which is costly and ineffective for daily use. In addition, there are several smartphone applications online, but they are not suitable for measuring the exact foot shape for custom footwear, both in clinical practice and public use. In this study, we designed and implemented computer-vision-based smartphone application OptiFit that provides the functionality to automatically measure the four essential dimensions (length, width, arch height, and instep girth) of a human foot from images and 3D scans. We present an instep girth measurement algorithm, and we used a pixel per metric algorithm for measurement; these algorithms were accordingly integrated with the application. Afterwards, we evaluated our application using 19 medical-grade silicon foot models (12 males and 7 females) from different age groups. Our experimental evaluation shows that OptiFit could measure the length, width, arch height, and instep girth with an accuracy of 95.23%, 96.54%, 89.14%, and 99.52%, respectively. A two-tailed paired t-test was conducted, and only the instep girth dimension showed a significant discrepancy between the manual measurement (MM) and the application-based measurement (AM). We developed a linear regression model to adjust the error. Further, we performed comparative analysis demonstrating that there were no significant errors between MM and AM, and the application offers satisfactory performance as a foot-measuring application. Unlike other applications, the iOS application we developed, OptiFit, fulfils the requirements to automatically measure the exact foot dimensions for individually fitted footwear. Therefore, the application can facilitate proper foot measurement and enhance awareness to prevent foot-related problems caused by inappropriate footwear.

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Section: Background and Related Workmentioning

confidence: 99%

OptiFit: Computer-Vision-Based Smartphone Application to Measure the Foot from Images and 3D Scans

Rafiq

Hoque

Kabir

et al. 2022

Sensors

View full text Add to dashboard Cite

show abstract

“…Two-dimensional camera approaches [ 4 , 5 ] use a 2D image to measure the size of a foot. To be able to do this, either a reference object with known size must be in the image, or the camera position relative to the object as well as the intrinsic parameters of the camera must be known.…”

Section: Introductionmentioning

confidence: 99%

Experimental Analysis of Commercial Optical Methods for Foot Measurement

Jager

Eberhardt

Cunningham

2022

Sensors

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Due to the increasing trend of online shopping, shoes are more and more often bought without being tried on. This leads to a strong increase in returns, which results in a high financial as well as ecological burden. To prevent this, feet can be measured either in the store or at home by various systems to determine the exact dimensions of the foot and derive an optimal shoe size. In this paper, we want to present an overview of the methods currently available on the market for the measurement of feet. The most important commercial systems are classified according to the underlying basic technology. Subsequently, the most promising methods were implemented and tested. The results of the different methods were finally compared to find out the strengths and weaknesses of each technology. After determining the measurement accuracy of the length and width for each measurement method and also comparing the general shape of the 3D reconstruction with the GT, it can be said that the measurement using a ToF sensor is currently the most robust, the easiest and, among other methods, the most accurate method.

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3D foot scanning using multiple RealSense cameras

Yuan

et al. 2020

Multimed Tools Appl

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Foot measurements from 2D digital images

Cited by 4 publications

References 2 publications

OptiFit: Computer-Vision-Based Smartphone Application to Measure the Foot from Images and 3D Scans

OptiFit: Computer-Vision-Based Smartphone Application to Measure the Foot from Images and 3D Scans

Experimental Analysis of Commercial Optical Methods for Foot Measurement

3D foot scanning using multiple RealSense cameras

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