Face-to-BMI: Using Computer Vision to Infer Body Mass Index on Social Media
March 09, 2017 Β· Declared Dead Β· π International Conference on Web and Social Media
"No code URL or promise found in abstract"
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Authors
Enes Kocabey, Mustafa Camurcu, Ferda Ofli, Yusuf Aytar, Javier Marin, Antonio Torralba, Ingmar Weber
arXiv ID
1703.03156
Category
cs.HC: Human-Computer Interaction
Cross-listed
cs.CV,
cs.CY
Citations
78
Venue
International Conference on Web and Social Media
Last Checked
3 months ago
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.
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