Literature DB >> 29623867

Image-based food portion size estimation using a smartphone without a fiducial marker.

Yifan Yang1, Wenyan Jia1, Tamara Bucher2, Hong Zhang3, Mingui Sun1.   

Abstract

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 (P0·05).
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.

Entities:  

Keywords:  Augmented reality; Dietary assessment; Image processing; International Food Unit™; Smartphone

Mesh:

Year:  2018        PMID: 29623867     DOI: 10.1017/S136898001800054X

Source DB:  PubMed          Journal:  Public Health Nutr        ISSN: 1368-9800            Impact factor:   4.022


  5 in total

1.  Perspective: Opportunities and Challenges of Technology Tools in Dietary and Activity Assessment: Bridging Stakeholder Viewpoints.

Authors:  Sai Krupa Das; Akari J Miki; Caroline M Blanchard; Edward Sazonov; Cheryl H Gilhooly; Sujit Dey; Colton B Wolk; Chor San H Khoo; James O Hill; Robin P Shook
Journal:  Adv Nutr       Date:  2022-02-01       Impact factor: 11.567

2.  Acceptability, Usability and Weight Loss Outcomes in a Randomized Cross-Over Study of Commercially Available Portion Size Tools in an Overweight South Asian Community.

Authors:  Basma Ellahi; Amanda Aitken; Derya Dikmen; Bilge Seyhan-Erdoğan; Munibah Makda; Rifat Razaq
Journal:  Int J Environ Res Public Health       Date:  2022-06-23       Impact factor: 4.614

3.  Man or machine? Will the digital transition be able to automatize dietary intake data collection?

Authors:  Bent Egberg Mikkelsen
Journal:  Public Health Nutr       Date:  2019-05       Impact factor: 4.022

4.  A Novel Approach to Dining Bowl Reconstruction for Image-Based Food Volume Estimation.

Authors:  Wenyan Jia; Yiqiu Ren; Boyang Li; Britney Beatrice; Jingda Que; Shunxin Cao; Zekun Wu; Zhi-Hong Mao; Benny Lo; Alex K Anderson; Gary Frost; Megan A McCrory; Edward Sazonov; Matilda Steiner-Asiedu; Tom Baranowski; Lora E Burke; Mingui Sun
Journal:  Sensors (Basel)       Date:  2022-02-15       Impact factor: 3.576

Review 5.  Current Developments in Digital Quantitative Volume Estimation for the Optimisation of Dietary Assessment.

Authors:  Wesley Tay; Bhupinder Kaur; Rina Quek; Joseph Lim; Christiani Jeyakumar Henry
Journal:  Nutrients       Date:  2020-04-22       Impact factor: 5.717

  5 in total

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