Sensors (Jul 2020)

goFOOD<sup>TM</sup>: An Artificial Intelligence System for Dietary Assessment

  • Ya Lu,
  • Thomai Stathopoulou,
  • Maria F. Vasiloglou,
  • Lillian F. Pinault,
  • Colleen Kiley,
  • Elias K. Spanakis,
  • Stavroula Mougiakakou

DOI
https://doi.org/10.3390/s20154283
Journal volume & issue
Vol. 20, no. 15
p. 4283

Abstract

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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.

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