Estimating Body Mass Index From Facial Images

Abstract

A person's health status may have a significant impact on many aspects of their life, from mental health to lifespan to financial security. The health of a person can be calculated by a value which is called Body Mass Index (BMI), it uses both the height and weight of a person. Numerous variables, including physical health, mental health, and popularity, have been linked to BMI. With the increasing number of people being obese, self-diagnostic solutions for healthy weight monitoring are grabbing significant attention. Calculating BMI using the statistical formula requires precise measurements of the height and weight of a person and is time-consuming. The main objective of this study is to predict the BMI of a person by giving the image as input. While developing Fitness apps, we can use this system to detect the BMI of a person daily and suggest suitable exercises. The developed system can also be used to find whether a person is suffering from malnutrition and some other diseases that can be detected using BMI. The models used in this study are FaceNet, Ridge Linear Regression, Random Forest Regression, Support Vector Regression, and ensemble of regression models.