Face-to-BMI: Using Computer Vision to Infer Body Mass Index on Social Media (1703.03156v1)
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.
- Enes Kocabey (1 paper)
- Mustafa Camurcu (2 papers)
- Ferda Ofli (37 papers)
- Yusuf Aytar (36 papers)
- Javier Marin (13 papers)
- Antonio Torralba (178 papers)
- Ingmar Weber (66 papers)