A simple vision based anthropometric estimation system using webcam

Abstract

Anthropometry can be defined as the science of dimensional measurement of the size and proportions of the human body. Anthropometric measurement is used in a lot of fields such as medical, forensics and clothing. The modern anthropometry techniques are expensive and takes up a lot of space while traditional anthropometry techniques are slow and susceptible to human error. Hence, there is a need for the development of a vision-based estimation system that is cheap, fast, accurate and portable. The study in this project proposes a noble way of using Raspberry 3B+ with Logitech C310 camera to perform estimation of chest, waist, hip circumference and body height through 2D images. The system works by implementing Pixel Density Method, HSV thresholding method, OpenPose deep neural network, bounding box method, pixel counting method and Ramanujans ellipse circumference approximation method to achieve objectives of this study. The percentage error between the estimated result and the measured result of chest, waist, hip circumference and body height are only 2.11%, 4.66%, 4.31% and 1.74%. In conclusion, a vision based anthropometric estimation system is successfully developed with high accuracy using all the proposed methods.