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The Use of Temporal Information in Food Image Analysis

  • Yu Wang
  • Ye He
  • Fengqing Zhu
  • Carol Boushey
  • Edward Delp
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9281)

Abstract

We have developed a dietary assessment system that uses food images captured by a mobile device. Food identification is a crucial component of our system. Achieving a high classification rates is challenging due to the large number of food categories and variability in food appearance. In this paper, we propose to improve food classification by incorporating temporal information. We employ recursive Bayesian estimation to incrementally learn from a person’s eating history. We show an improvement of food classification accuracy by 11% can be achieved.

Keywords

Mobile Device Temporal Information Accuracy Improvement Food Category Temporal Context 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Yu Wang
    • 1
  • Ye He
    • 2
  • Fengqing Zhu
    • 1
  • Carol Boushey
    • 3
  • Edward Delp
    • 1
  1. 1.School of Electrical and Computer EngineeringPurdue UniversityWest LafayetteUSA
  2. 2.GoogleMountain ViewUSA
  3. 3.Cancer Epidemiology ProgramUniversity of Hawaii Cancer CenterHonoluluUSA

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