Bootstrapping analysis of crowdsourced non-expert estimates of the number of calories in photographs of meals

RR Bond, Anne Moorhead, Huiru Zheng, Patrick McAllister

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

A total of 1800 estimates from non-expert dietitians were collected online. This comprised of 120 subjects each providing an estimate per image (120 subjects * 15 images). The overall aim of this study was to use crowdsourcing to determine the accuracy of non-experts in estimating calories in a meal as shown in a photograph. We analyzed percentiles and used bootstrapping with replacement to determine the typical percentile rank estimate that is in proximity to the ground truth and to determine the least number of sample estimates from a crowd of non-experts that can provide a convenient and accurate estimate of the number of calories in a meal.
Original languageEnglish
Title of host publication2018 IEEE International Conference on Bioinformatics and Biomedicine(BIBM 2018)
Place of PublicationMadrid, Spain
PublisherIEEE
Pages1465-1469
ISBN (Electronic)978-1-5386-5488-0
ISBN (Print)978-1-5386-5489-7
DOIs
Publication statusPublished - 3 Dec 2018

Keywords

  • Crowdsourcing
  • obesity
  • standards
  • estimation
  • conferences
  • bioinformatics
  • Gold

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