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.
- Publication:
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arXiv e-prints
- Pub Date:
- March 2017
- DOI:
- 10.48550/arXiv.1703.03156
- arXiv:
- arXiv:1703.03156
- Bibcode:
- 2017arXiv170303156K
- Keywords:
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- Computer Science - Human-Computer Interaction;
- Computer Science - Computer Vision and Pattern Recognition;
- Computer Science - Computers and Society
- E-Print:
- This is a preprint of a short paper accepted at ICWSM'17. Please cite that version instead