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Proceedings Paper

Automatic portion estimation and visual refinement in mobile dietary assessment
Author(s): Insoo Woo; Karl Otsmo; SungYe Kim; David S. Ebert; Edward J. Delp; Carol J. Boushey
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Paper 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.

Paper Details

Date Published: 27 January 2010
PDF: 10 pages
Proc. SPIE 7533, Computational Imaging VIII, 75330O (27 January 2010); doi: 10.1117/12.849051
Show Author Affiliations
Insoo Woo, Purdue Univ. (United States)
Karl Otsmo, Purdue Univ. (United States)
SungYe Kim, Purdue Univ. (United States)
David S. Ebert, Purdue Univ. (United States)
Edward J. Delp, Purdue Univ. (United States)
Carol J. Boushey, Purdue Univ. (United States)

Published in SPIE Proceedings Vol. 7533:
Computational Imaging VIII
Charles A. Bouman; Ilya Pollak; Patrick J. Wolfe, Editor(s)

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