Image-based Calorie Content Estimation for Dietary Assessment

Abstract

In this paper, we present an image-analysis based approach to calorie content estimation for dietary assessment. We make use of daily food images captured and stored by multiple users in a public Web service called FoodLog. The images are taken without any control or markers. We build a dictionary dataset of 6512 images contained in FoodLog the calorie content of which have been estimated by experts in nutrition. An image is compared to the ground truth data from the point of views of multiple image features such as color histograms, color correlograms and SURF fetures, and the ground truth images are ranked by similarities. Finally, calorie content of the input food image is computed by linear estimation using the top n ranked calories in multiple features. The distribution of the estimation shows that 79% of the estimations are correct within ±40% error and 35% correct within ±20% error.