- Title
- Image-based food portion size estimation using a smartphone without a fiducial marker
- Creator
- Yang, Yifan; Jia, Wenyan; Bucher, Tamara; Zhang, Hong; Sun, Mingui
- Relation
- Public Health Nutrition Vol. 22, Issue 7, p. 1180-1192
- Publisher Link
- http://dx.doi.org/10.1017/S136898001800054X
- Publisher
- Cambridge University Press
- Resource Type
- journal article
- Date
- 2019
- Description
- Objective: Current approaches to food volume estimation require the person to carry a fiducial marker (e.g. a checkerboard card), to be placed next to the food before taking a picture. This procedure is inconvenient and post-processing of the food picture is time-consuming and sometimes inaccurate. These problems keep people from using the smartphone for self-administered dietary assessment. The current bioengineering study presents a novel smartphone-based imaging approach to table-side estimation of food volume which overcomes current limitations. Design: We present a new method for food volume estimation without a fiducial marker. Our mathematical model indicates that, using a special picture-taking strategy, the smartphone-based imaging system can be calibrated adequately if the physical length of the smartphone and the output of the motion sensor within the device are known. We also present and test a new virtual reality method for food volume estimation using the International Food Unit™ and a training process for error control. Results: Our pilot study, with sixty-nine participants and fifteen foods, indicates that the fiducial-marker-free approach is valid and that the training improves estimation accuracy significantly (P<0·05) for all but one food (egg, P>0·05). Conclusions: Elimination of a fiducial marker and application of virtual reality, the International Food Unit™ and an automated training allowed quick food volume estimation and control of the estimation error. The estimated volume could be used to search a nutrient database and determine energy and nutrients in the diet.
- Subject
- dietary assessment; smartphone; image processing; international food unit; augmented reality
- Identifier
- http://hdl.handle.net/${Handle}
- Identifier
- uon:48611
- Identifier
- ISSN:1368-9800
- Language
- eng
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