CTADA: The design of a crowdsourcing tool for online food image identification and segmentation

© 2018 IEEE. Measuring accurate dietary intake, the process of determining what someone eats during the course of the day is considered to be an open research problem in the nutrition and health fields. We have developed image-based tools to automatically obtain accurate estimates of what foods and...

Full description

Bibliographic Details
Main Authors: Fang, S., Liu, C., Tahboub, K., Zhu, F., Delp, E., Boushey, Carol
Format: Conference Paper
Published: 2018
Online Access:http://hdl.handle.net/20.500.11937/73377
_version_ 1848762998076735488
author Fang, S.
Liu, C.
Tahboub, K.
Zhu, F.
Delp, E.
Boushey, Carol
author_facet Fang, S.
Liu, C.
Tahboub, K.
Zhu, F.
Delp, E.
Boushey, Carol
author_sort Fang, S.
building Curtin Institutional Repository
collection Online Access
description © 2018 IEEE. Measuring accurate dietary intake, the process of determining what someone eats during the course of the day is considered to be an open research problem in the nutrition and health fields. We have developed image-based tools to automatically obtain accurate estimates of what foods and how much energy/nutrients a user consumes. In this work, we present a crowdsourcing tool we designed and implemented to collect large sets of relevant online food images. This tool can be used to locate food items and obtaining groundtruth segmentation masks associated with all the foods presented in an image. We present a systematic design for a crowdsourcing tool aiming specifically for the task of online food image collection and annotations with a detailed description. The crowdsoucing tool we designed is tailored to meet the needs of building a large image dataset for developing automatic dietary assessment tools in the nutrition and health fields.
first_indexed 2025-11-14T10:56:28Z
format Conference Paper
id curtin-20.500.11937-73377
institution Curtin University Malaysia
institution_category Local University
last_indexed 2025-11-14T10:56:28Z
publishDate 2018
recordtype eprints
repository_type Digital Repository
spelling curtin-20.500.11937-733772018-12-13T09:35:31Z CTADA: The design of a crowdsourcing tool for online food image identification and segmentation Fang, S. Liu, C. Tahboub, K. Zhu, F. Delp, E. Boushey, Carol © 2018 IEEE. Measuring accurate dietary intake, the process of determining what someone eats during the course of the day is considered to be an open research problem in the nutrition and health fields. We have developed image-based tools to automatically obtain accurate estimates of what foods and how much energy/nutrients a user consumes. In this work, we present a crowdsourcing tool we designed and implemented to collect large sets of relevant online food images. This tool can be used to locate food items and obtaining groundtruth segmentation masks associated with all the foods presented in an image. We present a systematic design for a crowdsourcing tool aiming specifically for the task of online food image collection and annotations with a detailed description. The crowdsoucing tool we designed is tailored to meet the needs of building a large image dataset for developing automatic dietary assessment tools in the nutrition and health fields. 2018 Conference Paper http://hdl.handle.net/20.500.11937/73377 10.1109/SSIAI.2018.8470358 restricted
spellingShingle Fang, S.
Liu, C.
Tahboub, K.
Zhu, F.
Delp, E.
Boushey, Carol
CTADA: The design of a crowdsourcing tool for online food image identification and segmentation
title CTADA: The design of a crowdsourcing tool for online food image identification and segmentation
title_full CTADA: The design of a crowdsourcing tool for online food image identification and segmentation
title_fullStr CTADA: The design of a crowdsourcing tool for online food image identification and segmentation
title_full_unstemmed CTADA: The design of a crowdsourcing tool for online food image identification and segmentation
title_short CTADA: The design of a crowdsourcing tool for online food image identification and segmentation
title_sort ctada: the design of a crowdsourcing tool for online food image identification and segmentation
url http://hdl.handle.net/20.500.11937/73377