Paper Info
Title
goFOOD TM : An Artificial Intelligence System for Dietary Assessment.
Abstract
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.
Year
DOI
Venue
2020
10.3390/s20154283
SENSORS
Keywords
DocType
Volume
carbohydrate,protein,fat,calorie,nutrient estimation,computer vision,smartphone
Journal
20
Issue
ISSN
Citations 
15.0
1424-8220
0
PageRank 
References 
Authors
0.34
0
7
Name
Order
Citations
PageRank
Ya Lu122.74
Thomai Stathopoulou201.35
Maria F Vasiloglou300.34
Lillian F Pinault400.34
Colleen Kiley500.34
Elias K Spanakis600.34
Stavroula G Mougiakakou734228.61