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

RR Bond; Anne Moorhead; Huiru Zheng; Patrick McAllister

doi:10.1109/BIBM.2018.8621166

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

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-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 language	English
Title of host publication	Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018
Subtitle of host publication	Conference Proceedings
Editors	Harald Schmidt, David Griol, Haiying Wang, Jan Baumbach, Huiru Zheng, Zoraida Callejas, Xiaohua Hu, Julie Dickerson, Le Zhang
Place of Publication	Madrid, Spain
Publisher	IEEE
Pages	1465-1469
Number of pages	5
ISBN (Electronic)	978-1-5386-5488-0
DOIs	https://doi.org/10.1109/BIBM.2018.8621166
Publication status	Published (in print/issue) - 29 Jan 2019
Event	IEEE International Conference on Bioinformatics and Biomedicine (BIBM) - Madrid, Spain Duration: 3 Dec 2018 → 6 Dec 2018 http://orienta.ugr.es/bibm2018/

Conference

Conference	IEEE International Conference on Bioinformatics and Biomedicine (BIBM)
Country/Territory	Spain
City	Madrid
Period	3/12/18 → 6/12/18
Internet address	http://orienta.ugr.es/bibm2018/

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

crowdsourcing
food
digital health
food data analytics
data analytics
bootstrapping
calories
obesity

Access to Document

10.1109/BIBM.2018.8621166

Cite this

Bond, RR., Moorhead, A., Zheng, H., & McAllister, P. (2019). Bootstrapping analysis of crowdsourced non-expert estimates of the number of calories in photographs of meals. In H. Schmidt, D. Griol, H. Wang, J. Baumbach, H. Zheng, Z. Callejas, X. Hu, J. Dickerson, & L. Zhang (Eds.), Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018: Conference Proceedings (pp. 1465-1469). Article 8621166 IEEE. https://doi.org/10.1109/BIBM.2018.8621166

Bond, RR ; Moorhead, Anne ; Zheng, Huiru et al. / Bootstrapping analysis of crowdsourced non-expert estimates of the number of calories in photographs of meals. Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018: Conference Proceedings. editor / Harald Schmidt ; David Griol ; Haiying Wang ; Jan Baumbach ; Huiru Zheng ; Zoraida Callejas ; Xiaohua Hu ; Julie Dickerson ; Le Zhang. Madrid, Spain : IEEE, 2019. pp. 1465-1469

@inproceedings{d322fce3bbf44b269b3b545567b6f23f,

title = "Bootstrapping analysis of crowdsourced non-expert estimates of the number of calories in photographs of meals",

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.",

keywords = "crowdsourcing, food, digital health, food data analytics, data analytics, bootstrapping, calories, obesity",

author = "RR Bond and Anne Moorhead and Huiru Zheng and Patrick McAllister",

year = "2019",

month = jan,

day = "29",

doi = "10.1109/BIBM.2018.8621166",

language = "English",

pages = "1465--1469",

editor = "Harald Schmidt and David Griol and Haiying Wang and Jan Baumbach and Huiru Zheng and Zoraida Callejas and Xiaohua Hu and Julie Dickerson and Le Zhang",

booktitle = "Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018",

publisher = "IEEE",

address = "United States",

note = "IEEE International Conference on Bioinformatics and Biomedicine (BIBM) ; Conference date: 03-12-2018 Through 06-12-2018",

url = "http://orienta.ugr.es/bibm2018/",

}

Bond, RR , Moorhead, A , Zheng, H & McAllister, P 2019, Bootstrapping analysis of crowdsourced non-expert estimates of the number of calories in photographs of meals. in H Schmidt, D Griol, H Wang, J Baumbach, H Zheng, Z Callejas, X Hu, J Dickerson & L Zhang (eds), Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018: Conference Proceedings., 8621166, IEEE, Madrid, Spain, pp. 1465-1469, IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Madrid, Spain, 3/12/18. https://doi.org/10.1109/BIBM.2018.8621166

Bootstrapping analysis of crowdsourced non-expert estimates of the number of calories in photographs of meals. / Bond, RR ; Moorhead, Anne ; Zheng, Huiru et al.
Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018: Conference Proceedings. ed. / Harald Schmidt; David Griol; Haiying Wang; Jan Baumbach; Huiru Zheng; Zoraida Callejas; Xiaohua Hu; Julie Dickerson; Le Zhang. Madrid, Spain: IEEE, 2019. p. 1465-1469 8621166.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Bootstrapping analysis of crowdsourced non-expert estimates of the number of calories in photographs of meals

AU - Bond, RR

AU - Moorhead, Anne

AU - Zheng, Huiru

AU - McAllister, Patrick

PY - 2019/1/29

Y1 - 2019/1/29

N2 - 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.

AB - 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.

KW - crowdsourcing

KW - food

KW - digital health

KW - food data analytics

KW - data analytics

KW - bootstrapping

KW - calories

KW - obesity

UR - https://ieeexplore.ieee.org/abstract/document/8621166

UR - https://www.scopus.com/pages/publications/85062561341

U2 - 10.1109/BIBM.2018.8621166

DO - 10.1109/BIBM.2018.8621166

M3 - Conference contribution

SP - 1465

EP - 1469

BT - Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018

A2 - Schmidt, Harald

A2 - Griol, David

A2 - Wang, Haiying

A2 - Baumbach, Jan

A2 - Zheng, Huiru

A2 - Callejas, Zoraida

A2 - Hu, Xiaohua

A2 - Dickerson, Julie

A2 - Zhang, Le

PB - IEEE

CY - Madrid, Spain

T2 - IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

Y2 - 3 December 2018 through 6 December 2018

ER -

Bond RR , Moorhead A , Zheng H , McAllister P. Bootstrapping analysis of crowdsourced non-expert estimates of the number of calories in photographs of meals. In Schmidt H, Griol D, Wang H, Baumbach J, Zheng H, Callejas Z, Hu X, Dickerson J, Zhang L, editors, Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018: Conference Proceedings. Madrid, Spain: IEEE. 2019. p. 1465-1469. 8621166 doi: 10.1109/BIBM.2018.8621166

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

Abstract

Conference

UN SDGs

Keywords

Access to Document

Other files and links

Fingerprint

Deep learning-based food image classification and crowdsourcing-based calorie estimation approach to support dietary management

Cite this

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

Abstract

Conference

UN SDGs

Keywords

Access to Document

Other files and links

Fingerprint

Student theses

Deep learning-based food image classification and crowdsourcing-based calorie estimation approach to support dietary management

Cite this