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goFOOD(TM): An Artificial Intelligence System for Dietary Assessment
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 goFOOD(TM). The system can estimate the calorie and macronutrient content of a meal, on the sole basis of food...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7436102/ https://www.ncbi.nlm.nih.gov/pubmed/32752007 http://dx.doi.org/10.3390/s20154283 |
Sumario: | 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 goFOOD(TM). The system can estimate the calorie and macronutrient content of a meal, on the sole basis of food images captured by a smartphone. goFOOD(TM) 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. goFOOD(TM) 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 goFOOD(TM) performed better than experienced dietitians on the non-standardized meal database, and was comparable to them on the fast food database. goFOOD(TM) provides a simple and efficient solution to the end-user for dietary assessment. |
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