AI-enabled wearable cameras for assisting dietary assessment in African populations
Frank P-W Lo, Jianing Qiu, Modou L Jobarteh, Yingnan Sun, Zeyu Wang, Shuo Jiang, Tom Baranowski, Alex K Anderson, Megan A McCrory, Edward Sazonov, Wenyan Jia, Mingui Sun, Matilda Steiner-Asiedu, Gary Frost, Benny Lo · 2024
Read AI-enabled wearable cameras for assisting dietary assessment in African populations by Frank P-W Lo, Jianing Qiu, Modou L Jobarteh, Yingnan Sun, Zeyu Wang, Shuo Jiang, Tom Baranowski, Alex K Anderson, Megan A McCrory, Edward Sazonov, Wenyan Jia, Mingui Sun, Matilda Steiner-Asiedu, Gary Frost, Benny Lo (2024) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-11621677.txt.
Description
Frank Lo and a large team test wearable cameras for diet checks in African populations, in work published in 2024. Standard diet reports rely on memory and often miss true portion sizes. Their system, called EgoDiet, uses low cost cameras and egocentric vision to learn portion sizes from images.
Field studies ran in London and in Ghana with people of Ghanaian and Kenyan origin. In London, camera estimates beat dietitian estimates when judged by mean error for portion size. In Ghana, camera estimates also beat the standard day recall method on the same error measure. The team argues that passive cameras can serve as a practical stand in for older diet methods at population scale.
Catalog record
| CREATOR | Frank P-W Lo, Jianing Qiu, Modou L Jobarteh, Yingnan Sun, Zeyu Wang, Shuo Jiang, Tom Baranowski, Alex K Anderson, Megan A McCrory, Edward Sazonov, Wenyan Jia, Mingui Sun, Matilda Steiner-Asiedu, Gary Frost, Benny Lo |
|---|---|
| YEAR | 2024 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 88 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |