# Face-to-BMI: Using Computer Vision to Infer Body Mass Index on Social Media

arXiv: https://arxiv.org/abs/1703.03156 · HTML: https://mlsanity.com/paper/1703.03156/

## Key facts

- Cited by 9 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 9 Mar 2017.

## Built on by (most cited first, 9 of 9)

- [Collaborative Regression of Expressive Bodies using Moderation](https://mlsanity.com/paper/2105.05301/) (2021)
- [An Examination of Bias of Facial Analysis based BMI Prediction Models](https://mlsanity.com/paper/2204.10262/) (2022)
- [Estimation of BMI from Facial Images using Semantic Segmentation based Region-Aware Pooling](https://mlsanity.com/paper/2104.04733/) (2021)
- [MOFit: A Framework to reduce Obesity using Machine learning and IoT](https://mlsanity.com/paper/2108.08868/) (2021)
- [Towards Designing Computer Vision-based Explainable-AI Solution: A Use Case of Livestock Mart Industry](https://mlsanity.com/paper/2103.03096/) (2021)
- [Human Health Indicator Prediction from Gait Video](https://mlsanity.com/paper/2212.12948/) (2022)
- [PatchBMI-Net: Lightweight Facial Patch-based Ensemble for BMI Prediction](https://mlsanity.com/paper/2311.18102/) (2023)
- [BMI Prediction from Handwritten English Characters Using a Convolutional Neural Network](https://mlsanity.com/paper/2409.02584/) (2024)
- [Weight and Height Estimation from a Single Human Image Captured in the Wild](https://mlsanity.com/paper/2607.26104/) (2026)

## Abstract (arXiv)

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.