Computer vision-based food calorie estimation: dataset, method, and experiment

Computer vision has been introduced to estimate calories from food images. But current food image datasets dont contain volume and mass records of foods, which leads to an incomplete calorie estimation. In this paper, we present a novel food image dataset with volume and mass records of foods, and a deep learning method for food detection, to make a complete calorie estimation. Our dataset includes 2978 images, and every image contains corresponding each foods annotation, volume and mass records, as well as a certain calibration reference. To estimate calorie of food in the proposed dataset, a deep learning method using Faster R-CNN first is put forward to detect the food. And the experiment results show our method is effective to estimate calories and our dataset contains adequate information for calorie estimation. Our dataset is the first released food image dataset which can be used to evaluate computer vision-based calorie estimation methods.