Food image analysis: The big data problem you can eat!
© 2016 IEEE.Six of the ten leading causes of death in the United States can be directly linked to diet. Measuring accurate dietary intake, the process of determining what someone eats is considered to be an open research problem in the nutrition and health fields. We are developing image-based tools...
| Main Authors: | , , , , , , |
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| Format: | Conference Paper |
| Published: |
2017
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| Online Access: | http://hdl.handle.net/20.500.11937/52407 |
| _version_ | 1848758919035355136 |
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| author | Wang, Y. Fang, S. Liu, C. Zhu, F. Kerr, D. Boushey, Carol Delp, E. |
| author_facet | Wang, Y. Fang, S. Liu, C. Zhu, F. Kerr, D. Boushey, Carol Delp, E. |
| author_sort | Wang, Y. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | © 2016 IEEE.Six of the ten leading causes of death in the United States can be directly linked to diet. Measuring accurate dietary intake, the process of determining what someone eats is considered to be an open research problem in the nutrition and health fields. We are developing image-based tools in order to automatically obtain accurate estimates of what foods a user consumes. We have developed a novel food record application using the embedded camera in a mobile device. This paper describes the current status of food image analysis and overviews problems that still need to be addressed. |
| first_indexed | 2025-11-14T09:51:38Z |
| format | Conference Paper |
| id | curtin-20.500.11937-52407 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T09:51:38Z |
| publishDate | 2017 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-524072017-09-13T15:38:44Z Food image analysis: The big data problem you can eat! Wang, Y. Fang, S. Liu, C. Zhu, F. Kerr, D. Boushey, Carol Delp, E. © 2016 IEEE.Six of the ten leading causes of death in the United States can be directly linked to diet. Measuring accurate dietary intake, the process of determining what someone eats is considered to be an open research problem in the nutrition and health fields. We are developing image-based tools in order to automatically obtain accurate estimates of what foods a user consumes. We have developed a novel food record application using the embedded camera in a mobile device. This paper describes the current status of food image analysis and overviews problems that still need to be addressed. 2017 Conference Paper http://hdl.handle.net/20.500.11937/52407 10.1109/ACSSC.2016.7869576 restricted |
| spellingShingle | Wang, Y. Fang, S. Liu, C. Zhu, F. Kerr, D. Boushey, Carol Delp, E. Food image analysis: The big data problem you can eat! |
| title | Food image analysis: The big data problem you can eat! |
| title_full | Food image analysis: The big data problem you can eat! |
| title_fullStr | Food image analysis: The big data problem you can eat! |
| title_full_unstemmed | Food image analysis: The big data problem you can eat! |
| title_short | Food image analysis: The big data problem you can eat! |
| title_sort | food image analysis: the big data problem you can eat! |
| url | http://hdl.handle.net/20.500.11937/52407 |