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Proceedings Article

Automatic portion estimation and visual refinement in mobile dietary assessment

[+] Author Affiliations
Insoo Woo, Karl Otsmo, SungYe Kim, David S. Ebert, Edward J. Delp, Carol J. Boushey

Purdue Univ. (USA)

Proc. SPIE 7533, Computational Imaging VIII, 75330O (January 27, 2010); doi:10.1117/12.849051
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From Conference Volume 7533

  • Computational Imaging VIII
  • Charles A. Bouman; Ilya Pollak; Patrick J. Wolfe
  • San Jose, California | January 17, 2010

abstract

As concern for obesity grows, the need for automated and accurate methods to monitor nutrient intake becomes essential as dietary intake provides a valuable basis for managing dietary imbalance. Moreover, as mobile devices with built-in cameras have become ubiquitous, one potential means of monitoring dietary intake is photographing meals using mobile devices and having an automatic estimate of the nutrient contents returned. One of the challenging problems of the image-based dietary assessment is the accurate estimation of food portion size from a photograph taken with a mobile digital camera. In this work, we describe a method to automatically calculate portion size of a variety of foods through volume estimation using an image. These "portion volumes" utilize camera parameter estimation and model reconstruction to determine the volume of food items, from which nutritional content is then extrapolated. In this paper, we describe our initial results of accuracy evaluation using real and simulated meal images and demonstrate the potential of our approach.

© (2010) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.
Citation

Insoo Woo ; Karl Otsmo ; SungYe Kim ; David S. Ebert ; Edward J. Delp, et al.
"Automatic portion estimation and visual refinement in mobile dietary assessment", Proc. SPIE 7533, Computational Imaging VIII, 75330O (January 27, 2010); doi:10.1117/12.849051; http://dx.doi.org/10.1117/12.849051


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