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Detection and Recognition of Food in Photo Galleries for Analysis of User Preferences

  • Evgeniy MiasnikovEmail author
  • Andrey Savchenko
Conference paper
  • 133 Downloads
Part of the Lecture Notes in Computer Science book series (LNCS, volume 12131)

Abstract

Food analysis is one of the most important parts of user preference prediction engines for recommendation systems in the travel domain. In this paper, we describe and study the neural network method that allows you to recognize food in a gallery of photos taken with mobile devices. The described method consists of three main stages, including the classification of scenes, food detection, and subsequent classification. An essential feature of the developed method is the use of lightweight neural network models, which allows its usage on mobile devices. The development of the method was carried out using both known open data and a proprietary data set.

Keywords

Scene recognition Food detection Food recognition Convolutional neural networks (CNN) 

Notes

Acknowledgements

This research is based on the work supported by Samsung Research, Samsung Electronics.

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.St. Petersburg Department of Steklov Institute of MathematicsSt. PetersburgRussia
  2. 2.Laboratory of Algorithms and Technologies for Network AnalysisNational Research University Higher School of EconomicsNizhny NovgorodRussia

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