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FooDD: Food Detection Dataset for Calorie Measurement Using Food Images

  • Parisa PouladzadehEmail author
  • Abdulsalam Yassine
  • Shervin Shirmohammadi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9281)

Abstract

Food detection, classification, and analysis have been the topic of in-depth studies for a variety of applications related to eating habits and dietary assessment. For the specific topic of calorie measurement of food portions with single and mixed food items, the research community needs a dataset of images for testing and training. In this paper we introduce FooDD: a Food Detection Dataset of 3000 images that offer variety of food photos taken from different cameras with different illuminations. We also provide examples of food detection using graph cut segmentation and deep learning algorithms.

Keywords

Food image dataset Calorie measurement Food detection 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Parisa Pouladzadeh
    • 1
    Email author
  • Abdulsalam Yassine
    • 1
  • Shervin Shirmohammadi
    • 1
    • 2
  1. 1.Distributed and Collaborative Virtual Environments Research LaboratoryUniversity of OttawaOttawaCanada
  2. 2.Colleges of Engineering and Natural SciencesIstanbul Şehir UniversityIstanbulTurkey

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