EatAR tango: portion estimation on mobile devices with a depth sensor

PubDate: September 2017

Teams: Salzburg University of Applied Sciences

Writers: Radomir Dinic；Michael Domhardt；Simon Ginzinger；Thomas Stütz

PDF: EatAR tango: portion estimation on mobile devices with a depth sensor

Abstract

The accurate assessment of nutrition information is a challenging task, but crucial for people with certain diseases, such as diabetes. An important part of the assessment of nutrition information is portion estimation, i.e. volume estimation. Given the volume and the food type, the nutrition information can be computed on the basis of the food type specific nutrition density. Recently mobile devices with depth sensors have been made available for the public (Google’s project tango platform). In this work, an app for mobile devices with a depth sensor is presented which assists users in portion estimation. Furthermore, we present the design of a user study for the app and preliminary results.