goFOODTM: An Artificial Intelligence System for Dietary Assessment
| Autor: | Ya Lu, Thomai Stathopoulou, Maria F. Vasiloglou, Lillian F. Pinault, Colleen Kiley, Elias K. Spanakis, Stavroula Mougiakakou |
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| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: | |
| Zdroj: | Sensors, Vol 20, Iss 15, p 4283 (2020) |
| Druh dokumentu: | article |
| ISSN: | 20154283 1424-8220 |
| DOI: | 10.3390/s20154283 |
| Popis: | Accurate estimation of nutritional information may lead to healthier diets and better clinical outcomes. We propose a dietary assessment system based on artificial intelligence (AI), named goFOODTM. The system can estimate the calorie and macronutrient content of a meal, on the sole basis of food images captured by a smartphone. goFOODTM requires an input of two meal images or a short video. For conventional single-camera smartphones, the images must be captured from two different viewing angles; smartphones equipped with two rear cameras require only a single press of the shutter button. The deep neural networks are used to process the two images and implements food detection, segmentation and recognition, while a 3D reconstruction algorithm estimates the food’s volume. Each meal’s calorie and macronutrient content is calculated from the food category, volume and the nutrient database. goFOODTM supports 319 fine-grained food categories, and has been validated on two multimedia databases that contain non-standardized and fast food meals. The experimental results demonstrate that goFOODTM performed better than experienced dietitians on the non-standardized meal database, and was comparable to them on the fast food database. goFOODTM provides a simple and efficient solution to the end-user for dietary assessment. |
| Databáze: | Directory of Open Access Journals |
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