Dehais, Joachim Blaise; Shevchik, Sergey; Diem, Peter; Mougiakakou, Stavroula (November 2013). Food Volume Computation for Self Dietary Assessment Applications. In: 2013 IEEE 13th International Conference on Bioinformatics and Bioengineering (BIBE). Chania, Greece. 10.-13.11.2013.
Full text not available from this repository. (Request a copy)There is great demand for easily-accessible, user-friendly dietary self-management applications. Yet accurate, fully-automatic estimation of nutritional intake using computer vision methods remains an open research problem. One key element of this problem is the volume estimation, which can be computed from 3D models obtained using multi-view geometry. The paper presents a computational system for volume estimation based on the processing of two meal images. A 3D model of the served meal is reconstructed using the acquired images and the volume is computed from the shape. The algorithm was tested on food models (dummy foods) with known volume and on real served food. Volume accuracy was in the order of 90 %, while the total execution time was below 15 seconds per image pair. The proposed system combines simple and computational affordable methods for 3D reconstruction, remained stable throughout the experiments, operates in near real time, and places minimum constraints on users.
Item Type: |
Conference or Workshop Item (Paper) |
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Division/Institute: |
10 Strategic Research Centers > ARTORG Center for Biomedical Engineering Research > ARTORG Center - AI in Health and Nutrition 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, Shevchik, Sergey, Diem, Peter, Mougiakakou, Stavroula |
Subjects: |
600 Technology > 610 Medicine & health 600 Technology > 620 Engineering |
Submitter: |
Stavroula Mougiakakou |
Date Deposited: |
16 Jun 2014 17:18 |
Last Modified: |
05 Dec 2022 14:34 |
URI: |
https://boris.unibe.ch/id/eprint/52910 |
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