Food region detection using Bag-of-Features representation and color feature

Ruiko Miyano, Yuko Uematsu, Hideo Saito

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

6 Citations (Scopus)

Abstract

Food image processing has recently attracted attention, because many people take photos of food. For food image processing, recognition of captured food is an essential technology, but region detection of the food area from captured photos is also very important procedure for food recognition. In this paper, we propose a novel method for automatic region detection of food from photos using two kinds of features in input image. To detect food regions, we use a method which is widely used in generic object recognition. We divide an image into small subregions and represent each subregion as Bag-of-Features representation using local feature descriptors and color feature. Using two features, we recognize food subregions and finally connect them as food regions. Our experiments show that the proposed method can detect food region in high accuracy.

Original languageEnglish
Title of host publicationVISAPP 2012 - Proceedings of the International Conference on Computer Vision Theory and Applications
Pages709-713
Number of pages5
Publication statusPublished - 2012 Jun 15
EventInternational Conference on Computer Vision Theory and Applications, VISAPP 2012 - Rome, Italy
Duration: 2012 Feb 242012 Feb 26

Publication series

NameVISAPP 2012 - Proceedings of the International Conference on Computer Vision Theory and Applications
Volume1

Other

OtherInternational Conference on Computer Vision Theory and Applications, VISAPP 2012
Country/TerritoryItaly
CityRome
Period12/2/2412/2/26

Keywords

  • Bag-of-Features
  • Color feature
  • Food region detection
  • SURF
  • Support vector machine
  • Visual words

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design
  • Computer Vision and Pattern Recognition

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