AffiliationUniv Arizona, Dept Linguist
Univ Arizona, Dept Comp Sci
Univ Arizona, Dept Nutr Sci
MetadataShow full item record
PublisherJMIR PUBLICATIONS, INC
CitationZhou J, Bell D, Nusrat S, Hingle M, Surdeanu M, Kobourov S Calorie Estimation From Pictures of Food: Crowdsourcing Study Interact J Med Res 2018;7(2):e17 URL: https://www.i-jmr.org/2018/2/e17 DOI: 10.2196/ijmr.9359 PMID: 30401671 PMCID: 6246963
Rights©Jun Zhou, Dane Bell, Sabrina Nusrat, Melanie Hingle, Mihai Surdeanu, Stephen Kobourov. Originally published in the Interactive Journal of Medical Research (http://www.i-jmr.org/), 05.11.2018. This is an open-access article distributed under the terms of the Creative Commons Attribution License.
Collection InformationThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at email@example.com.
AbstractA total of 2028 respondents agreed to participate in the study (males: 770/2028, 37.97%, mean body mass index: 27.5 kg/m2). Average accuracy was 5 out of 20 correct guesses, where "correct" was defined as a number within 20% of the ground truth. Even a small crowd of 10 individuals achieved an accuracy of 7, exceeding the average individual and expert annotator's accuracy of 5. Women were more accurate than men (P<.001), and younger people were more accurate than older people (P<.001). The calorie content of energy-dense foods was overestimated (P=.02). Participants performed worse when images contained reference objects, such as credit cards, for scale (P=.01).
NoteOpen access journal
VersionFinal published version
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