Automated Binocular Vision Measurement of Food Dimensions and Volume for Dietary Evaluation

Abstract

We propose a novel binocular vision technique to obtain food dimensions for dietary evaluation. A wearable device acquired images of food samples, which were segmented using the improved Chan-Vese model and compared with virtual objects. Results showed this method to be robust, achieving higher accuracy than conventional correspondence techniques.