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dc.contributor.authorKocabey, Enes
dc.contributor.authorCamurcu, Mustafa
dc.contributor.authorOffli, Ferda
dc.contributor.authorAytar, Yusuf
dc.contributor.authorMarin, Javier
dc.contributor.authorTorralba, Antonio
dc.contributor.authorWeber, Ingmar
dc.date.accessioned2019-07-11T19:04:49Z
dc.date.available2019-07-11T19:04:49Z
dc.date.issued2017
dc.identifier.isbn978-1-57735-798-8
dc.identifier.issn2334-0770
dc.identifier.urihttps://hdl.handle.net/1721.1/121587
dc.description.abstractA 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.en_US
dc.language.isoen
dc.publisherAssociation for the Advancement of Artificial Intelligence Pressen_US
dc.relation.isversionofhttps://aaai.org/Library/ICWSM/icwsm17contents.phpen_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alikeen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/en_US
dc.sourcearXiven_US
dc.titleFace-to-BMI: Using computer vision to infer body mass index on social mediaen_US
dc.typeArticleen_US
dc.identifier.citationKocabey, Enes et al. "Face-to-BMI: Using computer vision to infer body mass index on social media." Proceedings of the Eleventh International Conference on Web and Social Media, May 2017, Montreal, Quebec, Canada, Association for the Advancement of Artificial Intelligence Press, 2017 © 2017 Association for the Advancement of Artificial Intelligence Pressen_US
dc.contributor.departmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratoryen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Scienceen_US
dc.relation.journalProceedings of the Eleventh International Conference on Web and Social Mediaen_US
dc.eprint.versionOriginal manuscripten_US
dc.type.urihttp://purl.org/eprint/type/ConferencePaperen_US
eprint.statushttp://purl.org/eprint/status/NonPeerRevieweden_US
dc.date.updated2019-07-11T16:22:41Z
dspace.date.submission2019-07-11T16:22:42Z


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