Food Volume Estimation for Quantifying Dietary Intake with a Wearable Camera

Anqi Gao1, Po Wen Lo2, Benny Lo1

  • 1Imperial College London
  • 2The Chinese University of Hong Kong

Details

15:15 - 15:30 | Tue 6 Mar | Antilles CD | TuBT1.5

Session: BSN Session # 4 – Wellness and Sports Applications

Abstract

A novel food volume measurement technique is proposed in this paper for accurate quantification of the daily dietary intake of the user. The technique is based on simultaneous localisation and mapping (SLAM), a modified version of convex hull algorithm, and a 3D mesh object reconstruction technique. This paper explores the feasibility of applying SLAM techniques for continuous food volume measurement with a monocular wearable camera. A sparse map will be generated by SLAM after capturing the images of the food item with the camera and the multiple convex hull algorithm is applied to form a 3D mesh object. The volume of the target object can then be computed based on the mesh object. Compared to previous volume measurement techniques, the proposed method can measure the food volume continuously with no prior knowledge. Experiments have been carried out to evaluate this new technique and showed the feasibility and accuracy of the proposed algorithm in measuring food volume.