A skeleton-free kinect system for body mass index assessment using deep neural networks

Abstract

In this paper we present a skeleton-free Kinect system to estimate body mass index (BMI) of human bodies. Unlike other systems in the literature, the proposed system does not require a scale to measure the weight. The weight of observed subjects are estimated using body surface area (BSA) regression. The proposed system employs the state-of-the-art deep residual network to extract meaningful features and estimate the BMI scores with a 95% accuracy.