Sensors, Vol. 20, Pages 4283: goFOODTM : An Artificial Intelligence System for Dietary Assessment

Sensors, Vol. 20, Pages 4283: goFOODTM : An Artificial Intelligence System for Dietary Assessment Sensors doi: 10.3390/s20154283 Authors: Ya Lu Thomai Stathopoulou Maria F. Vasiloglou Lillian F. Pinault Colleen Kiley Elias K. Spanakis Stavroula Mougiakakou 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 w...
Source: Sensors - Category: Biotechnology Authors: Tags: Article Source Type: research