Face-to-BMI: Using Computer Vision to Infer Body Mass Index on Social Media
Abstract
A person's weight status can have profound implications on their life, ranging from mental health, to longevity, to financial income. At the societal level, "fat shaming" and other forms of "sizeism" are a growing concern, while increasing obesity rates are linked to ever raising healthcare costs. For these reasons, researchers from a variety of backgrounds are interested in studying obesity from all angles. To obtain data, traditionally, a person would have to accurately self-report their body-mass index (BMI) or would have to see a doctor to have it measured. In this paper, we show how computer vision can be used to infer a person's BMI from social media images. We hope that our tool, which we release, helps to advance the study of social aspects related to body weight.
Cite
@article{arxiv.1703.03156,
title = {Face-to-BMI: Using Computer Vision to Infer Body Mass Index on Social Media},
author = {Enes Kocabey and Mustafa Camurcu and Ferda Ofli and Yusuf Aytar and Javier Marin and Antonio Torralba and Ingmar Weber},
journal= {arXiv preprint arXiv:1703.03156},
year = {2017}
}
Comments
This is a preprint of a short paper accepted at ICWSM'17. Please cite that version instead