Name
Abstract | ||
|---|---|---|
There is now convincing evidence that poor diet, in combination with physical inactivity are key determinants of an individual's risk of developing chronic diseases, such as obesity, cancer, cardiovascular disease or diabetes. Assessing what people eat is fundamental to establishing the link between diet and disease. Food records are considered the best approach for assessing energy intake. However, this method requires literate and highly motivated subjects and adolescents and young adults are the least likely to undertake food records. The ready access of the majority of the population to mobile phones has opened up new opportunities for dietary assessment. In such systems, the camera in the mobile phone is used for capturing images of food consumed and these images are then processed to automatically estimate the nutritional content of the food. A vital step in this process is the estimation of the volume of the food in the image. In this paper we propose a food volume estimation approach which requires only a pair of stereo images to be captured. Our experimental results show that the proposed approach can provide an accurate estimate of the volume of typical food items in a passive manner without the need for manual fitting of 3D models to the food items. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/SITIS.2012.146 | SITIS |
Keywords | Field | DocType |
food volume estimation approach,typical food item,best approach,accurate estimate,food record,mobile phone,chronic disease,cardiovascular disease,food item,food volume estimation,dietary assessment system,estimation theory | Population,Computer vision,Feature detection,Computer science,Volume estimation,Artificial intelligence,Mobile phone,Dietary assessment | Conference |
ISBN | Citations | PageRank |
978-1-4673-5152-2 | 1 | 0.36 |
References | Authors | |
0 | 7 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Md. Hafizur Rahman | 1 | 15 | 3.41 |
| Qiang Li | 2 | 1 | 0.36 |
| Mark Pickering | 3 | 1 | 0.36 |
| Michael Frater | 4 | 13 | 2.15 |
| Deborah Kerr | 5 | 1 | 0.36 |
| Carol Bouchey | 6 | 1 | 0.36 |
| Edward J. Delp | 7 | 2321 | 351.37 |