Face to BMI Prediction Using Machine Learning Algorithms

Abstract

bstract: BMI of a person is a gauge of how healthy they are in relation to their weight. Numerous aspects, including physical health, mental health, and popularity, have been linked to BMI. Accurate height and weight, is frequently necessary for BMI calculations which would need labor-intensive measurement. BMI is a key indicator of diseases that can develop as a result of greater body fat levels and is related to cholesterol and body fat. Governments and businesses can employ large-scale automation of BMI calculation to analyze many facets of society and to make smart decisions. Prior works have only used geometric facial features, disregarding other information, or a data-driven deep learning strategy where the amount of data becomes a limiting factor. From health industry till the social media applications, there are many areas where BMI data is used. Human faces contain a number of cues that are able to be a subject of a study. Hence, face image is used to predict BMI. In this study, a deep network-based BMI predictor tool is designed and its performance is evaluated using Convolutional Neural Networks (CNN) and Regression.