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Food log by analyzing food images

Published:26 October 2008Publication History

ABSTRACT

In this paper, a food-logging system that can distinguish food images from other images, analyze the food balance, and visualize the log is presented. The image processing is based on feature vectors consisting of color histograms, DCT coefficients, detected image patterns and so forth. Support Vector Machine (SVM) was used to detect food images and to analyze the food balance. Experimental results show that the food image extraction presents above 88% of accuracy and the food balance estimation is achieved with more than 73% of accuracy.

References

  1. D. Tancharoen, W. Puangpakisiri, T. Yamasaki, K. Aizawa, "Life log platform for continuous and discrete recording and retrieval of personal media," ECTI-EEC Transactions, vol.5, no.2, pp.165--173, August, 2007.Google ScholarGoogle Scholar
  2. G.C. De Silva, T. Yamasaki, K. Aiazawa, "An interactive multimedia diary for the home," IEEE Computer, Special issue on human centered computing, vol.40, issue 5, pp.52--59, May 2007. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. J. Gemmell, G. Bell, R. Lueder, S. Drucker, C. Wong, "MyLifeBits: fulfilling the memex vision," Proc. the 10th ACM international conference on Multimedia, pp. 235--238, 2002. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. mypyramid.gov, United States Department of Agriculture, http://www.mypyramid.gov/Google ScholarGoogle Scholar

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  1. Food log by analyzing food images

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    • Published in

      cover image ACM Conferences
      MM '08: Proceedings of the 16th ACM international conference on Multimedia
      October 2008
      1206 pages
      ISBN:9781605583037
      DOI:10.1145/1459359

      Copyright © 2008 ACM

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 26 October 2008

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      Overall Acceptance Rate995of4,171submissions,24%

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