التفاصيل البيبلوغرافية
| العنوان: |
Egocentric Image Captioning for Privacy-Preserved Passive Dietary Intake Monitoring. |
| المؤلفون: |
Qiu J, Lo FP, Gu X, Jobarteh ML, Jia W, Baranowski T, Steiner-Asiedu M, Anderson AK, McCrory MA, Sazonov E, Sun M, Frost G, Lo B |
| المصدر: |
IEEE transactions on cybernetics [IEEE Trans Cybern] 2024 Feb; Vol. 54 (2), pp. 679-692. Date of Electronic Publication: 2024 Jan 17. |
| نوع المنشور: |
Journal Article |
| اللغة: |
English |
| بيانات الدورية: |
Publisher: Institute of Electrical and Electronics Engineers Country of Publication: United States NLM ID: 101609393 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2168-2275 (Electronic) Linking ISSN: 21682267 NLM ISO Abbreviation: IEEE Trans Cybern Subsets: MEDLINE |
| أسماء مطبوعة: |
Original Publication: New York, NY : Institute of Electrical and Electronics Engineers, 2013- |
| مواضيع طبية MeSH: |
Privacy* , Eating*, Diet ; Nutrition Assessment ; Feeding Behavior |
| مستخلص: |
Camera-based passive dietary intake monitoring is able to continuously capture the eating episodes of a subject, recording rich visual information, such as the type and volume of food being consumed, as well as the eating behaviors of the subject. However, there currently is no method that is able to incorporate these visual clues and provide a comprehensive context of dietary intake from passive recording (e.g., is the subject sharing food with others, what food the subject is eating, and how much food is left in the bowl). On the other hand, privacy is a major concern while egocentric wearable cameras are used for capturing. In this article, we propose a privacy-preserved secure solution (i.e., egocentric image captioning) for dietary assessment with passive monitoring, which unifies food recognition, volume estimation, and scene understanding. By converting images into rich text descriptions, nutritionists can assess individual dietary intake based on the captions instead of the original images, reducing the risk of privacy leakage from images. To this end, an egocentric dietary image captioning dataset has been built, which consists of in-the-wild images captured by head-worn and chest-worn cameras in field studies in Ghana. A novel transformer-based architecture is designed to caption egocentric dietary images. Comprehensive experiments have been conducted to evaluate the effectiveness and to justify the design of the proposed architecture for egocentric dietary image captioning. To the best of our knowledge, this is the first work that applies image captioning for dietary intake assessment in real-life settings. |
| تواريخ الأحداث: |
Date Created: 20230407 Date Completed: 20240118 Latest Revision: 20240118 |
| رمز التحديث: |
20240118 |
| DOI: |
10.1109/TCYB.2023.3243999 |
| PMID: |
37028043 |
| قاعدة البيانات: |
MEDLINE |
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