MT-Diet: Automated smartphone based diet assessment with infrared images

Research output: Chapter in Book/Report/Conference proceedingConference contribution

13 Scopus citations

Abstract

In this paper, we propose MT-Diet, a smartphone-based automated diet monitoring system that interfaces a thermal camera with a smartphone and identifies types of food consumed at the click of a button. The system uses thermal maps of a food plate to increase accuracy of segmentation and extraction of food parts, and combines thermal and visual images to improve accuracy in the detection of cooked food. Test results on 80 different types of cooked food show that MT-Diet can isolate food parts with an accuracy of 97.5% and determine the type of food with an accuracy of 88.93%, which is a significant improvement (nearly 25%) over the state-of-the-art.

Original languageEnglish (US)
Title of host publication2016 IEEE International Conference on Pervasive Computing and Communications, PerCom 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Print)9781467387798
DOIs
StatePublished - Apr 19 2016
Event14th IEEE International Conference on Pervasive Computing and Communications, PerCom 2016 - Sydney, Australia
Duration: Mar 14 2016Mar 19 2016

Other

Other14th IEEE International Conference on Pervasive Computing and Communications, PerCom 2016
CountryAustralia
CitySydney
Period3/14/163/19/16

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications
  • Human-Computer Interaction

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  • Cite this

    Lee, J., Banerjee, A., & Gupta, S. (2016). MT-Diet: Automated smartphone based diet assessment with infrared images. In 2016 IEEE International Conference on Pervasive Computing and Communications, PerCom 2016 [7456506] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/PERCOM.2016.7456506