Two-view 3D Reconstruction for Food Volume Estimation

Dehais, Joachim Blaise; Anthimopoulos, Marios; Shevchik, Sergey; Mougiakakou, Stavroula (2017). Two-view 3D Reconstruction for Food Volume Estimation. IEEE transactions on multimedia, 19(5), pp. 1090-1099. Institute of Electrical and Electronics Engineers 10.1109/TMM.2016.2642792

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The increasing prevalence of diet-related chronic diseases coupled with the ineffectiveness of traditional diet management methods have resulted in a need for novel tools to accurately and automatically assess meals. Recently, computer vision based systems that use meal images to assess their content have been proposed. Food portion estimation is the most difficult task for individuals assessing their meals and it is also the least studied area. The present paper proposes a three-stage system to calculate portion sizes using two images of a dish acquired by mobile devices. The first stage consists in understanding the configuration of the different views, after which a dense 3D model is built from the two images; finally, this 3D model serves to extract the volume of the different items. The system was extensively tested on 77 real dishes of known volume, and achieved an average error of less than 10% in 5.5 seconds per dish. The proposed pipeline is computationally tractable and requires no user input, making it a viable option for fully automated dietary assessment.

Item Type:

Journal Article (Original Article)

Division/Institute:

10 Strategic Research Centers > ARTORG Center for Biomedical Engineering Research > ARTORG Center - Diabetes Technology
04 Faculty of Medicine > Department of Intensive Care, Emergency Medicine and Anaesthesiology (DINA) > University Emergency Center
04 Faculty of Medicine > Department of Gynaecology, Paediatrics and Endocrinology (DFKE) > Clinic of Endocrinology, Diabetology and Clinical Nutrition

Graduate School:

Graduate School for Cellular and Biomedical Sciences (GCB)

UniBE Contributor:

Dehais, Joachim Blaise; Anthimopoulos, Marios; Shevchik, Sergey and Mougiakakou, Stavroula

Subjects:

600 Technology > 610 Medicine & health
600 Technology > 620 Engineering

ISSN:

1520-9210

Publisher:

Institute of Electrical and Electronics Engineers

Funders:

[UNSPECIFIED] FP7

Language:

English

Submitter:

Stavroula Mougiakakou

Date Deposited:

27 Dec 2016 13:30

Last Modified:

21 Sep 2017 13:35

Publisher DOI:

10.1109/TMM.2016.2642792

URI:

https://boris.unibe.ch/id/eprint/92131

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